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HERMES AGENT CAN CREATE VIDEOS. NOT WITH AN API CALL. IT WRITES THE CODE, RENDERS THE SCENES, AND STITCHES THEM INTO AN MP4. the video attached to this post was generated by Hermes Agent using manim-video skill. three bundled video skills most people skip: 1. MANIM VIDEO 3Blue1Brown-style animated...

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YanXbt

4,548 subscribers

33,817 görüntüleme • 4 ay önce •via X (Twitter)

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Johnny Nel | AI for Founders profil fotoğrafı
Johnny Nel | AI for Founders4 ay önce

most founders miss this... AI agents writing their own code without you lifting a finger is the real leverage

YanXbt profil fotoğrafı
YanXbt4 ay önce

@JohnnyNel_ It really is. I have my Hermes multiple tasks with different models which suits better for every task and I went to enjoy my day while he was working for me 😍

Alviss Ambassador to NAF0 profil fotoğrafı
Alviss Ambassador to NAF04 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

please open your dm i can`t send you a message

Alviss Ambassador to NAF0 profil fotoğrafı
Alviss Ambassador to NAF04 ay önce

done

YanXbt profil fotoğrafı
YanXbt4 ay önce

all done🚀

ţară ♿☸🎡 { 𝔅ℜ𝔊 } profil fotoğrafı
ţară ♿☸🎡 { 𝔅ℜ𝔊 }4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

check your DM 🚀

Nahid profil fotoğrafı
Nahid4 ay önce

manim-style videos with zero GPU sounds wild

YanXbt profil fotoğrafı
YanXbt4 ay önce

It is wild you need to try it yourself

KHOA AI | HILL profil fotoğrafı
KHOA AI | HILL4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your dm 🚀

Alexandre Nascimento profil fotoğrafı
Alexandre Nascimento4 ay önce

MANIN

YanXbt profil fotoğrafı
YanXbt4 ay önce

check your dm 🚀

Charlie · 云马AI · 免🪜稳连 Claude/GPT/Gemini API profil fotoğrafı
Charlie · 云马AI · 免🪜稳连 Claude/GPT/Gemini API4 ay önce

这个我挺认同的，视频生成不一定非得端到端黑盒。像 manim 这种让代理写代码再渲染，反而更可控，改一个公式、一个镜头都很清楚，特别适合做解释类内容。

YanXbt profil fotoğrafı
YanXbt4 ay önce

especially for video with technical/process explanations and workflow showcases

T. Dawei profil fotoğrafı
T. Dawei4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your inbox 🚀

Renan Silverio profil fotoğrafı
Renan Silverio4 ay önce

Manim

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your dm 🚀

Nick Venturi profil fotoğrafı
Nick Venturi4 ay önce

writing python to render videos directly is so much better than spamming prompts 😅

hodeehum profil fotoğrafı
hodeehum4 ay önce

MANIM

GonAI profil fotoğrafı
GonAI2 ay önce

MANIM

ib profil fotoğrafı
ib4 ay önce

Manim

Red Pak🛸 profil fotoğrafı
Red Pak🛸3 ay önce

manim

Benzer Videolar

I've combined Manim Nous Research's Hermes Agent skill + 's Math Code. Math Code executes the proof on a problem called Jordan's Lemma and Hermes Agent with Claude Sonnet 3.7 directs Math Code, writes a script, gets Manim to render an explanatory video. Jordan's Lemma: It helps to simplify high-dimensional problems by breaking them down into manageable, 2D pieces. The lemma is the underlying mathematical reason why Grover's Algorithm (useful in quantum) works by rotating within a 2D plane. Rendered explanation video below:
0:24

I've combined Manim Nous Research's Hermes Agent skill + 's Math Code. Math Code executes the proof on a problem called Jordan's Lemma and Hermes Agent with Claude Sonnet 3.7 directs Math Code, writes a script, gets Manim to render an explanatory video. Jordan's Lemma: It helps to simplify high-dimensional problems by breaking them down into manageable, 2D pieces. The lemma is the underlying mathematical reason why Grover's Algorithm (useful in quantum) works by rotating within a 2D plane. Rendered explanation video below:

Jeanne

142,115 görüntüleme • 6 ay önce

I've spend 10+ hrs perfecting how to get the best out of Opus 5.5 for video generation workflow: - Use it with Claude Code, not the app. - Use OpenRouter API to access all the other models (image gen, video gen, audio gen) with one key - Use Gemini 3.8 TTS and make it create a skill from the API to put emotion into the voice. - Use Manim, Hyperframes, Motion Canvas for motion graphics for HTML web grounded video - Use GPT 2.5 Image Sunburst for keyframes and Veo 3.1 / Seedance 2.5 for generation. Seedance does better with motion shots. Ensure you have reference images for consistency and generate an animatic before full video. - Add a script writing planning skill. Use OpenTimelineIO to assemble. - Explicitly tell it to avoid Claudisms like short punchy sentences and a lot of numbers. “Narrate like a university professor.” - Allow it to use yt-dlp with search to inject clips from real videos (creative commons) in composition - Use ElevenLabs for music gen in the background - Add a caption skill which uses any decent ASR model to get word-level timed subtitles on the final video - Add a critic skill which takes screenshots and uses transcription to validation the audio and video quality In the prompt, specify a) what you want b) aspect ratio c) length d) style preferences. ffmpeg handles most of the actual video manipulation tasks. Here's an example of a 4 minute Neocloud business explainer:
4:00

I've spend 10+ hrs perfecting how to get the best out of Opus 5.5 for video generation workflow: - Use it with Claude Code, not the app. - Use OpenRouter API to access all the other models (image gen, video gen, audio gen) with one key - Use Gemini 3.8 TTS and make it create a skill from the API to put emotion into the voice. - Use Manim, Hyperframes, Motion Canvas for motion graphics for HTML web grounded video - Use GPT 2.5 Image Sunburst for keyframes and Veo 3.1 / Seedance 2.5 for generation. Seedance does better with motion shots. Ensure you have reference images for consistency and generate an animatic before full video. - Add a script writing planning skill. Use OpenTimelineIO to assemble. - Explicitly tell it to avoid Claudisms like short punchy sentences and a lot of numbers. “Narrate like a university professor.” - Allow it to use yt-dlp with search to inject clips from real videos (creative commons) in composition - Use ElevenLabs for music gen in the background - Add a caption skill which uses any decent ASR model to get word-level timed subtitles on the final video - Add a critic skill which takes screenshots and uses transcription to validation the audio and video quality In the prompt, specify a) what you want b) aspect ratio c) length d) style preferences. ffmpeg handles most of the actual video manipulation tasks. Here's an example of a 4 minute Neocloud business explainer:

Deedy

156,204 görüntüleme • 20 gün önce

this is pure f*cking treasure Netflix engineers posted 20 GitHub repos that turn your Opus 5.5 into a f*cking motion empire: built for Opus 5.5 1. claude-motion: taste, checks its own frames, sound written in code. the author built it for Opus 5.5 2. claude-motion-design: HTML, Playwright and ffmpeg, no Remotion. the demo was made on Opus 5.5 3. motion-graphics-skills: 13 skills for launch videos. the README tells you to run it on Opus 5.5 4. claude-remotion-skill: a Remotion editor from one prompt. captions, B-roll, sound 5. klik-anim-skill-creation: the laws of animation and camera, built on Opus 6. hyperframes-motion-reel-skill: a showreel cut to the beat at 120 BPM, on HyperFrames 7. product-launch-motion: a full launch film. voice-over, camera, color grade 8. animate: a short clip in one canvas file, storyboarded as it goes 9. motion-design-skills: timing, color, typography, logos, Remotion 10. hyperframes-student-kit: 14 skills and 406 motion graphics cards the engines these skills render with 11. hyperframes: HTML to MP4. the one almost everyone installs 12. remotion: video written in React 13. remotion skills: the official Remotion skills for your agent 14. GSAP: the timelines HyperFrames runs on. skills: npx skills add greensock/gsap-skills taste and everything around it 15. motion-design-skill: motion principles that work with any engine 16. awesome-motion-design-agent-skills: a map of GSAP, Remotion, Lottie and Rive skills 17. motion-graphics: B-roll built straight from your transcript 18. motion-dev-animations-skill: web animation on not video 19. motion: Motion itself, formerly Framer Motion 20. lottie-web: when you need Lottie, not MP4 the stack in one line: Opus 5.5 writes the code, a skill sets the timing and the camera, an engine renders the MP4. check each repo before you install. save this.
0:22

this is pure f*cking treasure Netflix engineers posted 20 GitHub repos that turn your Opus 5.5 into a f*cking motion empire: built for Opus 5.5 1. claude-motion: taste, checks its own frames, sound written in code. the author built it for Opus 5.5 2. claude-motion-design: HTML, Playwright and ffmpeg, no Remotion. the demo was made on Opus 5.5 3. motion-graphics-skills: 13 skills for launch videos. the README tells you to run it on Opus 5.5 4. claude-remotion-skill: a Remotion editor from one prompt. captions, B-roll, sound 5. klik-anim-skill-creation: the laws of animation and camera, built on Opus 6. hyperframes-motion-reel-skill: a showreel cut to the beat at 120 BPM, on HyperFrames 7. product-launch-motion: a full launch film. voice-over, camera, color grade 8. animate: a short clip in one canvas file, storyboarded as it goes 9. motion-design-skills: timing, color, typography, logos, Remotion 10. hyperframes-student-kit: 14 skills and 406 motion graphics cards the engines these skills render with 11. hyperframes: HTML to MP4. the one almost everyone installs 12. remotion: video written in React 13. remotion skills: the official Remotion skills for your agent 14. GSAP: the timelines HyperFrames runs on. skills: npx skills add greensock/gsap-skills taste and everything around it 15. motion-design-skill: motion principles that work with any engine 16. awesome-motion-design-agent-skills: a map of GSAP, Remotion, Lottie and Rive skills 17. motion-graphics: B-roll built straight from your transcript 18. motion-dev-animations-skill: web animation on not video 19. motion: Motion itself, formerly Framer Motion 20. lottie-web: when you need Lottie, not MP4 the stack in one line: Opus 5.5 writes the code, a skill sets the timing and the camera, an engine renders the MP4. check each repo before you install. save this.

NO1ennn

478,060 görüntüleme • 11 gün önce

The more agents and projects you have running, the harder it gets to keep track of everything through chat alone. This is where Hermes Kanban comes in. Here's how Hermes Kanban works, why it's worth using, and how I'd recommend setting it up: Chat is where you work with an agent. Kanban is where you manage the work across agents. Hermes Kanban gives you a visual dashboard for tracking tasks across your agents and projects. But it's much more than a task board. Here's what you can do with it: • Create tasks and assign them to specific Hermes agents. • Track what's ready, running, blocked, or completed. • Set dependencies so tasks wait for other work to finish. • Coordinate handoffs between specialized agents. • Review progress and see where something needs your attention. And with the dispatcher, Hermes can pick up tasks that are ready to run and launch the appropriate agent to handle them. Now, here's something I'd recommend: **Create a separate Kanban board for each major project.** For example: 📌 Content production Research → Drafting → Review → Assets → Done 📌 Software development Bugs → Features → Testing → Review → Done 📌 Business operations Research → Waiting → In Progress → Blocked → Done Hermes supports multiple isolated boards, so each project can have its own tasks, workspaces, logs, and agent workflows. You can also connect a board to a Hermes Project to keep the work tied to the right project context. The more work you hand off to Hermes, the more valuable this becomes. Instead of digging through conversations trying to figure out what every agent is doing, give each project its own board and manage the work from one place. 🎥 Video credit: Tom
2:03

The more agents and projects you have running, the harder it gets to keep track of everything through chat alone. This is where Hermes Kanban comes in. Here's how Hermes Kanban works, why it's worth using, and how I'd recommend setting it up: Chat is where you work with an agent. Kanban is where you manage the work across agents. Hermes Kanban gives you a visual dashboard for tracking tasks across your agents and projects. But it's much more than a task board. Here's what you can do with it: • Create tasks and assign them to specific Hermes agents. • Track what's ready, running, blocked, or completed. • Set dependencies so tasks wait for other work to finish. • Coordinate handoffs between specialized agents. • Review progress and see where something needs your attention. And with the dispatcher, Hermes can pick up tasks that are ready to run and launch the appropriate agent to handle them. Now, here's something I'd recommend: **Create a separate Kanban board for each major project.** For example: 📌 Content production Research → Drafting → Review → Assets → Done 📌 Software development Bugs → Features → Testing → Review → Done 📌 Business operations Research → Waiting → In Progress → Blocked → Done Hermes supports multiple isolated boards, so each project can have its own tasks, workspaces, logs, and agent workflows. You can also connect a board to a Hermes Project to keep the work tied to the right project context. The more work you hand off to Hermes, the more valuable this becomes. Instead of digging through conversations trying to figure out what every agent is doing, give each project its own board and manage the work from one place. 🎥 Video credit: Tom

Hermes Release Watch

27,640 görüntüleme • 9 gün önce

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video
0:43

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

Peter Yang

70,122 görüntüleme • 4 ay önce

HERMES AGENT LEARNS FROM ITS OWN MISTAKES. UPDATES ITS MEMORY. CREATES ITS OWN SKILLS. NO CLOUD. EVERYTHING STORED LOCALLY. THIS IS HOW THE SELF-IMPROVING LOOP WORKS. most agents start from zero every session. Hermes carries forward what it learned. THREE MEMORY SYSTEMS: 1. PROCEDURAL MEMORY (how to act) stored in ~/.hermes/skills/ as SKILL.md files. when the agent repeats a complex workflow, it saves the procedure as a reusable skill. next time the same task comes up, it follows the skill instead of figuring it out again. you can also create skills explicitly: "create a skill called video-prep that captures how I format my video scripts. spoken english, define jargon inline, no em-dashes, close with a catchphrase." the agent writes the SKILL.md. available as a slash command from that moment. Hermes ships with 90+ skills. the number grows the longer you use it. 2. SEMANTIC MEMORY (durable facts about you) stored in ~/.hermes/memory/memory.md the agent scans conversations for facts worth remembering. preferences, habits, corrections, project details. real example from the video: agent tried to scrape a YouTube channel. URL was wrong. it failed. it updated memory.md with the correct URL pattern so it never makes the same mistake again. you can also save explicitly: "save to memory that my favorite testing framework is pytest" the agent updates memory.md immediately. this file loads into context on every session. the agent knows you better every week. 3. EPISODIC MEMORY (chat history) stored in ~/.hermes/state.db (local SQLite). every conversation. every tool call. every result. searchable with FTS5 full-text search. "search our past sessions. what was the first thing I ever said to you?" the agent queries state.db and finds it. over time, auxiliary models consolidate episodic memory into semantic memory. distilling recurring patterns into durable facts. THE SELF-IMPROVING LOOP: every agent run follows this cycle: → you send a prompt → working memory loads: SOUL.md + memory.md + relevant skills + chat history → agent calls tools (terminal, browser, delegate_task) → agent completes the task, replies to you → AFTER the reply: agent checks "did I learn something worth saving?" → if yes: updates memory.md or creates a new skill → next session starts smarter than the last this happens automatically. you don't ask the agent to learn. it decides what to remember on its own. WHAT MAKES THIS DIFFERENT FROM CLAUDE CODE: Claude Code has memory too. but Hermes stores everything locally. no cloud. your data never leaves your machine. Claude Code doesn't auto-create skills from experience. Hermes turns repeated workflows into reusable procedures. Claude Code memory is instruction-based. Hermes memory is conversational and self-updating. over months of usage, Hermes builds a knowledge base of your preferences, your projects, your mistakes, and the procedures that work for your specific workflow. the agent that remembers your birthday also remembers why your last deploy failed. NO EMBEDDINGS. PLAIN TEXT. Hermes does not use embeddings or RAG for memory. skill and memory search runs on plain text keyword matching. simpler. faster. no vector database to maintain. works entirely offline on your local machine. DELEGATE TO CLAUDE CODE: Hermes can spawn a sub-agent that runs Claude Code in headless mode: "spawn a sub-agent using Claude CLI to build a Python script that fetches the top 5 Hacker News stories to markdown." Hermes delegates. Claude Code writes the code. result returns to Hermes. Hermes runs the script and delivers the output. use Hermes for orchestration. use Claude Code for heavy coding. both tools. not competitors. WHAT HERMES DOES NOT HAVE: no built-in eval or LMOps system. no LangSmith, no LangFuse integration out of the box. trajectory export and logs exist but there is no automated quality tracking. if you need eval, build it yourself or connect external tools. the loop is self-improving. measuring how well it improves is on you. comment LOOP and I'll send you the configs that control how fast Hermes learns and what it remembers. memory limits, skill auto-creation triggers, and the auxiliary model that runs the learning. Replace your entire team with 8 hermes agents👇
20:54

HERMES AGENT LEARNS FROM ITS OWN MISTAKES. UPDATES ITS MEMORY. CREATES ITS OWN SKILLS. NO CLOUD. EVERYTHING STORED LOCALLY. THIS IS HOW THE SELF-IMPROVING LOOP WORKS. most agents start from zero every session. Hermes carries forward what it learned. THREE MEMORY SYSTEMS: 1. PROCEDURAL MEMORY (how to act) stored in ~/.hermes/skills/ as SKILL.md files. when the agent repeats a complex workflow, it saves the procedure as a reusable skill. next time the same task comes up, it follows the skill instead of figuring it out again. you can also create skills explicitly: "create a skill called video-prep that captures how I format my video scripts. spoken english, define jargon inline, no em-dashes, close with a catchphrase." the agent writes the SKILL.md. available as a slash command from that moment. Hermes ships with 90+ skills. the number grows the longer you use it. 2. SEMANTIC MEMORY (durable facts about you) stored in ~/.hermes/memory/memory.md the agent scans conversations for facts worth remembering. preferences, habits, corrections, project details. real example from the video: agent tried to scrape a YouTube channel. URL was wrong. it failed. it updated memory.md with the correct URL pattern so it never makes the same mistake again. you can also save explicitly: "save to memory that my favorite testing framework is pytest" the agent updates memory.md immediately. this file loads into context on every session. the agent knows you better every week. 3. EPISODIC MEMORY (chat history) stored in ~/.hermes/state.db (local SQLite). every conversation. every tool call. every result. searchable with FTS5 full-text search. "search our past sessions. what was the first thing I ever said to you?" the agent queries state.db and finds it. over time, auxiliary models consolidate episodic memory into semantic memory. distilling recurring patterns into durable facts. THE SELF-IMPROVING LOOP: every agent run follows this cycle: → you send a prompt → working memory loads: SOUL.md + memory.md + relevant skills + chat history → agent calls tools (terminal, browser, delegate_task) → agent completes the task, replies to you → AFTER the reply: agent checks "did I learn something worth saving?" → if yes: updates memory.md or creates a new skill → next session starts smarter than the last this happens automatically. you don't ask the agent to learn. it decides what to remember on its own. WHAT MAKES THIS DIFFERENT FROM CLAUDE CODE: Claude Code has memory too. but Hermes stores everything locally. no cloud. your data never leaves your machine. Claude Code doesn't auto-create skills from experience. Hermes turns repeated workflows into reusable procedures. Claude Code memory is instruction-based. Hermes memory is conversational and self-updating. over months of usage, Hermes builds a knowledge base of your preferences, your projects, your mistakes, and the procedures that work for your specific workflow. the agent that remembers your birthday also remembers why your last deploy failed. NO EMBEDDINGS. PLAIN TEXT. Hermes does not use embeddings or RAG for memory. skill and memory search runs on plain text keyword matching. simpler. faster. no vector database to maintain. works entirely offline on your local machine. DELEGATE TO CLAUDE CODE: Hermes can spawn a sub-agent that runs Claude Code in headless mode: "spawn a sub-agent using Claude CLI to build a Python script that fetches the top 5 Hacker News stories to markdown." Hermes delegates. Claude Code writes the code. result returns to Hermes. Hermes runs the script and delivers the output. use Hermes for orchestration. use Claude Code for heavy coding. both tools. not competitors. WHAT HERMES DOES NOT HAVE: no built-in eval or LMOps system. no LangSmith, no LangFuse integration out of the box. trajectory export and logs exist but there is no automated quality tracking. if you need eval, build it yourself or connect external tools. the loop is self-improving. measuring how well it improves is on you. comment LOOP and I'll send you the configs that control how fast Hermes learns and what it remembers. memory limits, skill auto-creation triggers, and the auxiliary model that runs the learning. Replace your entire team with 8 hermes agents👇

YanXbt

23,088 görüntüleme • 3 ay önce

You may recall that a few months ago, I posted about yet another project of mine where I decided to make a ground-up, memory-safe Rust implementation of the manim math animation system used by 3Blue1Brown to make all his awesome math explainer videos on YouTube (see quoted post below). The original manim project is a sort of dog's breakfast amalgamation of a bunch of random software, including LaTeX and a bunch of Python and other stuff. I got rid of ALL of that and did everything from scratch, including all the typesetting. That's almost absurdly ambitious if you dig into the details. No LaTeX! All that stuff is done from scratch as part of my FrankenMarkdown project, all the numerical stuff (using FrankenNumpy and FrankenPandas and other projects of mine), etc. The one thing I decided to not reinvent is the video encoding, where it calls out to ffmpeg. Everything else is part of one compact rust cli tool and library, which weighs in at just 12.4 megabytes. Well anyway, I started the project around 3 months ago and made sure to always keep it going every single day with a few agents, as I do with over 100+ other projects I have going on at any given time. The thing is, I'm so busy with other projects, I just can't get into the weeds for stuff like this on a day-to-day basis. Once the plan is completed and turned into beads, it's basically just auto-pilot. It's already I run my /reality-check-for-project skill on all my projects a few times per week, so I knew in the abstract that the project was getting pretty close to finished, and then today I decided to dig in a bit and see where things stood. To test it, I asked Claude Opus 5.5 to build the latest FrankenManim version on my Mac and then use it to create a nice 3b1b-style explainer video about one of my favorite things in math, Hoeffding's D. I had the nice idea of using FrankenTTS to provide the narration rather than just have a silent video, which added a nice dimension to it. Anyway, everything works just amazingly well and I'm totally blown away by how good it is and how dramatically better and faster this new toolchain is than using the "agglomeration of junk" approach from the legacy manim system (no offense, that's just the reality of it... just downloading all the software used by legacy manim is many, many gigs of software written in tons of different languages, filled with bugs and weird compatibility gotchas and bound together with digital duct tape and bailing wire: "legacy manim plus MacTeX, which its docs recommend, is a 7.0 GB download and 10.9 GB installed"). By comparison, FrankenManim is one single memory-safe Rust binary that's just 12.4mb and that does it ALL (other than video encoding), that's cross-platform, that can even be compiled into wasm and run in a browser (try doing THAT with legacy manim!). And it's fast: the whole 30,431-frame 4K60 video renders in 141 seconds on my Threadripper with two 4090s GPUs. This is the way of the future. And the entire FrankenManim project is built out of my other projects: asupersync as the foundation, FrankenMarkdown, FrankenNumpy, FrankenPandas, FrankenSciPy, FrankenNetworkX, FrankenTorch, the list goes on and on. Everything is cumulative and builds on itself. I didn't even have FrankenTTS when I created the plan for FrankenManim, but now that I do, I think I'll bundle that in (it's also distributed as a library) to make it easier to add narration to your explainer videos. I'll also make a skill soon for my skills site that automates the entire process end to end of making an explainer video like this. You can either supply the script yourself or just say what you want covered and any other details and the agent can do the rest itself, fully autonomously. Perhaps it's time that people start paying attention to my approach and master plan here instead of dismissing it all as "slop" and "AI psychosis." I don't see my critics replacing all of manim with a single tiny binary, or really doing anything interesting or valuable to anyone for that matter.
8:27

You may recall that a few months ago, I posted about yet another project of mine where I decided to make a ground-up, memory-safe Rust implementation of the manim math animation system used by 3Blue1Brown to make all his awesome math explainer videos on YouTube (see quoted post below). The original manim project is a sort of dog's breakfast amalgamation of a bunch of random software, including LaTeX and a bunch of Python and other stuff. I got rid of ALL of that and did everything from scratch, including all the typesetting. That's almost absurdly ambitious if you dig into the details. No LaTeX! All that stuff is done from scratch as part of my FrankenMarkdown project, all the numerical stuff (using FrankenNumpy and FrankenPandas and other projects of mine), etc. The one thing I decided to not reinvent is the video encoding, where it calls out to ffmpeg. Everything else is part of one compact rust cli tool and library, which weighs in at just 12.4 megabytes. Well anyway, I started the project around 3 months ago and made sure to always keep it going every single day with a few agents, as I do with over 100+ other projects I have going on at any given time. The thing is, I'm so busy with other projects, I just can't get into the weeds for stuff like this on a day-to-day basis. Once the plan is completed and turned into beads, it's basically just auto-pilot. It's already I run my /reality-check-for-project skill on all my projects a few times per week, so I knew in the abstract that the project was getting pretty close to finished, and then today I decided to dig in a bit and see where things stood. To test it, I asked Claude Opus 5.5 to build the latest FrankenManim version on my Mac and then use it to create a nice 3b1b-style explainer video about one of my favorite things in math, Hoeffding's D. I had the nice idea of using FrankenTTS to provide the narration rather than just have a silent video, which added a nice dimension to it. Anyway, everything works just amazingly well and I'm totally blown away by how good it is and how dramatically better and faster this new toolchain is than using the "agglomeration of junk" approach from the legacy manim system (no offense, that's just the reality of it... just downloading all the software used by legacy manim is many, many gigs of software written in tons of different languages, filled with bugs and weird compatibility gotchas and bound together with digital duct tape and bailing wire: "legacy manim plus MacTeX, which its docs recommend, is a 7.0 GB download and 10.9 GB installed"). By comparison, FrankenManim is one single memory-safe Rust binary that's just 12.4mb and that does it ALL (other than video encoding), that's cross-platform, that can even be compiled into wasm and run in a browser (try doing THAT with legacy manim!). And it's fast: the whole 30,431-frame 4K60 video renders in 141 seconds on my Threadripper with two 4090s GPUs. This is the way of the future. And the entire FrankenManim project is built out of my other projects: asupersync as the foundation, FrankenMarkdown, FrankenNumpy, FrankenPandas, FrankenSciPy, FrankenNetworkX, FrankenTorch, the list goes on and on. Everything is cumulative and builds on itself. I didn't even have FrankenTTS when I created the plan for FrankenManim, but now that I do, I think I'll bundle that in (it's also distributed as a library) to make it easier to add narration to your explainer videos. I'll also make a skill soon for my skills site that automates the entire process end to end of making an explainer video like this. You can either supply the script yourself or just say what you want covered and any other details and the agent can do the rest itself, fully autonomously. Perhaps it's time that people start paying attention to my approach and master plan here instead of dismissing it all as "slop" and "AI psychosis." I don't see my critics replacing all of manim with a single tiny binary, or really doing anything interesting or valuable to anyone for that matter.

Jeffrey Emanuel

19,473 görüntüleme • 12 gün önce

Been using Nous Research Hermes Agent for media editing and it completely replaced my workflow. You know the drill : - Trim a video - open CapCut. - Convert to mp3 - another site. - Remove audio - another one. - Make a gif - yet another one. - more tasks, more different tools minutes of uploading and downloading.. Now you can do all of that just by chatting like asking a designer friend to edit your media and getting it back instantly :) I built a media toolset for Hermes that handles all of this natively. It registers as a skill inside the agent - Hermes sees your video, understands what you're asking, takes the right operations and use the best skills and give you what you really wanted perfectly ▪️ Trim any segment down to the second ▪️ Speed up or slow down with pitch corrected audio ▪️ Compress without destroying quality ▪️ Create a gif on defined times range ▪️ Cut the video and rotate it and apply instagram ▪️ Convert between any format - mp4, mp3, ogg, webm ▪️ Chain edits: "trim 0:30 1:00 and speed up 1.5x and compress" ▪️ Burn .srt subtitles directly into the video ▪️ Add or remove text watermarks with custom position ▪️ Generate thumbnails from any timestamp ▪️ Fade in/out with custom duration ▪️ ASCII video art with multiple character styles and many more with customizable skills Works the same on Telegram, Discord, WhatsApp etc. This is what agents should be doing and Hermes does.
3:01

Been using Nous Research Hermes Agent for media editing and it completely replaced my workflow. You know the drill : - Trim a video - open CapCut. - Convert to mp3 - another site. - Remove audio - another one. - Make a gif - yet another one. - more tasks, more different tools minutes of uploading and downloading.. Now you can do all of that just by chatting like asking a designer friend to edit your media and getting it back instantly :) I built a media toolset for Hermes that handles all of this natively. It registers as a skill inside the agent - Hermes sees your video, understands what you're asking, takes the right operations and use the best skills and give you what you really wanted perfectly ▪️ Trim any segment down to the second ▪️ Speed up or slow down with pitch corrected audio ▪️ Compress without destroying quality ▪️ Create a gif on defined times range ▪️ Cut the video and rotate it and apply instagram ▪️ Convert between any format - mp4, mp3, ogg, webm ▪️ Chain edits: "trim 0:30 1:00 and speed up 1.5x and compress" ▪️ Burn .srt subtitles directly into the video ▪️ Add or remove text watermarks with custom position ▪️ Generate thumbnails from any timestamp ▪️ Fade in/out with custom duration ▪️ ASCII video art with multiple character styles and many more with customizable skills Works the same on Telegram, Discord, WhatsApp etc. This is what agents should be doing and Hermes does.

ogichain

11,291 görüntüleme • 7 ay önce

Motion graphics used to take me an hour per scene (or more) Now I'm creating them in 3-5 minutes — without After Effects, without Premiere, without writing a single line of code. I'm a former LA filmmaker (still PGA). My entire video stack is now 3 tools: Claude Code + HyperFrames (from HeyGen) + Descript Here's how the workflow runs: 1. Drop my brand style guide into a folder (colors, fonts, components Claude reuses forever) 2. Paste a line from my Descript transcript into Claude Code: "Create a scene for this part of the video" 3. Claude Code reads my brand, generates the HyperFrames scene, renders it to MP4 4. Drag the MP4 into Descript, drop it on the matching line of the transcript 5. Done. 3-5 minutes per scene. The unlock is the brand style guide. Once Claude has your colors, fonts, and reusable components, every scene inherits your look automatically. Bonus — you can take a Claude Design export (.zip), hand it to Claude Code, and it'll convert the HTML into a HyperFrames video you can render and edit. I built a GitHub repo with all the skills pre-loaded. Non-developers can clone it, open Claude Code, and be rendering scenes in under 10 minutes. Full walkthrough (20 min video) below Repo (skills + brand template + music-from-transcript plugin): Bookmark this if you make videos. The brand-style-guide pattern alone will save you hours every week. If you're a creator or operator using AI for content — share this with someone who's still living in After Effects.
23:55

Motion graphics used to take me an hour per scene (or more) Now I'm creating them in 3-5 minutes — without After Effects, without Premiere, without writing a single line of code. I'm a former LA filmmaker (still PGA). My entire video stack is now 3 tools: Claude Code + HyperFrames (from HeyGen) + Descript Here's how the workflow runs: 1. Drop my brand style guide into a folder (colors, fonts, components Claude reuses forever) 2. Paste a line from my Descript transcript into Claude Code: "Create a scene for this part of the video" 3. Claude Code reads my brand, generates the HyperFrames scene, renders it to MP4 4. Drag the MP4 into Descript, drop it on the matching line of the transcript 5. Done. 3-5 minutes per scene. The unlock is the brand style guide. Once Claude has your colors, fonts, and reusable components, every scene inherits your look automatically. Bonus — you can take a Claude Design export (.zip), hand it to Claude Code, and it'll convert the HTML into a HyperFrames video you can render and edit. I built a GitHub repo with all the skills pre-loaded. Non-developers can clone it, open Claude Code, and be rendering scenes in under 10 minutes. Full walkthrough (20 min video) below Repo (skills + brand template + music-from-transcript plugin): Bookmark this if you make videos. The brand-style-guide pattern alone will save you hours every week. If you're a creator or operator using AI for content — share this with someone who's still living in After Effects.

JJ Englert

103,908 görüntüleme • 6 ay önce

MASSIVE Hermes Agent update over the last few days Totally changes the way I use Hermes Here's 6 new features you need to start using immediately (video demoing them below): 1. Mixture of agents: send your prompt to a team of different models. The team sends back all of their responses to an orchestrator model who synthesizes a final answer. Gives much better results than just sending a prompt to 1 model 2. /learn: use the new built in /learn skill to have Hermes automatically create new skills. You can either give a prompt after /learn or put in a URL. I like pasting in URLs of tweets with helpful tips after /learn and Hermes will automatically turn it into a skill 3. /journey: See every skill and memory Hermes has created for you on a really nice timeline/chart. Great for seeing how your agent has learned and improved over time 4. Self improvement cost savings: Hermes now uses cheaper models to do it's self improvement including memory creation and skill creation. These types of activities happen in the background of almost every prompt, so this results in TONS of cost savings over time 5. Vibe coding improvements: Hermes desktop is now a full vibe coding tool. You can see diffs, make commits, and even open up PRs directly from the desktop interface. Makes it WAYYY nicer to vibe code with 6. Fable 5 is now built in. Fable 5. Obviously Fable is incredibly expensive, so only use this new profile for incredibly complex tasks. Excellent updates that have significantly improved the experience. Video demoing all the updates below!
11:56

MASSIVE Hermes Agent update over the last few days Totally changes the way I use Hermes Here's 6 new features you need to start using immediately (video demoing them below): 1. Mixture of agents: send your prompt to a team of different models. The team sends back all of their responses to an orchestrator model who synthesizes a final answer. Gives much better results than just sending a prompt to 1 model 2. /learn: use the new built in /learn skill to have Hermes automatically create new skills. You can either give a prompt after /learn or put in a URL. I like pasting in URLs of tweets with helpful tips after /learn and Hermes will automatically turn it into a skill 3. /journey: See every skill and memory Hermes has created for you on a really nice timeline/chart. Great for seeing how your agent has learned and improved over time 4. Self improvement cost savings: Hermes now uses cheaper models to do it's self improvement including memory creation and skill creation. These types of activities happen in the background of almost every prompt, so this results in TONS of cost savings over time 5. Vibe coding improvements: Hermes desktop is now a full vibe coding tool. You can see diffs, make commits, and even open up PRs directly from the desktop interface. Makes it WAYYY nicer to vibe code with 6. Fable 5 is now built in. Fable 5. Obviously Fable is incredibly expensive, so only use this new profile for incredibly complex tasks. Excellent updates that have significantly improved the experience. Video demoing all the updates below!

Alex Finn

143,999 görüntüleme • 3 ay önce

Claude Code can ship a 45-second animated explainer ad in 30 minutes. No video editor needed, just CC + skills. Here's how I made this video for Soteri Skin 👇 1. /plan Concept Brief (Claude Code) I handwrite a concept brief, then chat with the agent to iterate on it. The agent gathers any raw materials we might need - context about the brand, product images, end card, etc. The concept brief details the concept, characters, visual style, script, etc 2. /prepare a moodboard (CC + GPT Image 2 + ElevenLabs) After reviewing the script, generate: - character reference images - voiceover samples for the characters / narrator - the storyboard (scene by scene grid) - a few keyframe scenes 3. /generate Keyframes for each scene (CC uses Nano Banana or GPT Image 2) Uses the character references from the previous step to generate keyframes for each scene. I probably should have done a round of iteration at this step – there's some character drift and the pH meter representation could have been better. 4. /animate Keyframe → Animated Clip (CC uses Fal Seedance) Generate 2-4 representative scenes first to see a preview. If it looks good, then generate everything. 5. /stitch (CC + ffmpeg + ElevenLabs) - Stitch clips together with hard cut - Add a music score + SFX - Sync clips to the VO - Add captions - Review and edit timing / pacing issues 6. /watch the final cut and review it - as a video editor for technical errors (mismatched voiceover and visuals, AI hallucinations, etc) - as a viewer (ICP). I delegate most of the review to the agent because it catches more things and keeps me out of the loop as much as possible. It also fixes any issues found in the review. That's it. This video took me 30 minutes because I have already created skills for everything I described above. Some day, this will be < 5 minutes. I just review and chat to provide direction and feedback. The skills do all the technical work. 7. /learn Extracts learnings and updates the skills. This final step is really important. It turns this process into a closed loop system that makes the next video much easier to create because all the learnings from the human-in-the-loop process get encoded into code. Skills are code too. If you want access to the skill, drop a comment, and I'll DM it to you (must be following). If you want to make AI video ads like this, DM me.
0:45

Claude Code can ship a 45-second animated explainer ad in 30 minutes. No video editor needed, just CC + skills. Here's how I made this video for Soteri Skin 👇 1. /plan Concept Brief (Claude Code) I handwrite a concept brief, then chat with the agent to iterate on it. The agent gathers any raw materials we might need - context about the brand, product images, end card, etc. The concept brief details the concept, characters, visual style, script, etc 2. /prepare a moodboard (CC + GPT Image 2 + ElevenLabs) After reviewing the script, generate: - character reference images - voiceover samples for the characters / narrator - the storyboard (scene by scene grid) - a few keyframe scenes 3. /generate Keyframes for each scene (CC uses Nano Banana or GPT Image 2) Uses the character references from the previous step to generate keyframes for each scene. I probably should have done a round of iteration at this step – there's some character drift and the pH meter representation could have been better. 4. /animate Keyframe → Animated Clip (CC uses Fal Seedance) Generate 2-4 representative scenes first to see a preview. If it looks good, then generate everything. 5. /stitch (CC + ffmpeg + ElevenLabs) - Stitch clips together with hard cut - Add a music score + SFX - Sync clips to the VO - Add captions - Review and edit timing / pacing issues 6. /watch the final cut and review it - as a video editor for technical errors (mismatched voiceover and visuals, AI hallucinations, etc) - as a viewer (ICP). I delegate most of the review to the agent because it catches more things and keeps me out of the loop as much as possible. It also fixes any issues found in the review. That's it. This video took me 30 minutes because I have already created skills for everything I described above. Some day, this will be < 5 minutes. I just review and chat to provide direction and feedback. The skills do all the technical work. 7. /learn Extracts learnings and updates the skills. This final step is really important. It turns this process into a closed loop system that makes the next video much easier to create because all the learnings from the human-in-the-loop process get encoded into code. Skills are code too. If you want access to the skill, drop a comment, and I'll DM it to you (must be following). If you want to make AI video ads like this, DM me.

Shiv

11,760 görüntüleme • 4 ay önce

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.
0:26

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.

Kid Pak

59,475 görüntüleme • 5 ay önce

Video content creation sounds simple, but what if you don’t have time to: • Write the script, • Prepare the visuals, • Generate the voiceover, • Create the subtitles, • And finally render the video? This is why we built Noustiny on top of Nous Research Hermes Agent by adding 12 generic Hermes tools + 13 generic Hermes skills, bringing the whole process into one single flow. How does it work? Let’s take a closer look 👇 ———— 1- Story state: context, tree, motifs: Hermes had no built-in narrative-state primitive for tracking canon, branching story structure, and recurring motifs. So we added three generic Hermes tools for this: → story_tree_graph: Manages the story tree structure. It handles operations like canon path, descendants, and splice insertion points. → narrative_context_builder: Walks the canon chain and returns the live context every narrative skill should reason against. This includes recent chain, mood, and character state. → motif_tracker: Remembers recurring motifs across the story arc. For example, a sword introduced in beat 2 can reappear meaningfully in later scenes. ———— 2- Character / cast pipeline: Hermes had no built-in primitive for cast extraction or character continuity. So we added a four-tool character pipeline: → story_copyright_detector: Handles IP scrubbing. For example, “Iron Man” is converted into an IP-free character description before the image API ever sees it. → character_sheet_builder: Produces 1 to 4 characters. For each character, it creates an IP-free visual description and a hero-portrait prompt. These portraits become the reference frames used across later storyboard scenes. → character_registry_lookup: Finds a character by name inside the cast sheet and attaches the correct portrait reference to each beat. → character_alias_resolver: Resolves aliases like “Mr. Stark” into the main character name. This way, the same character keeps one portrait reference even if they appear under different names. ———— 3- Voice pipeline: Hermes had no built-in primitive for audio acquisition or voice cloning. So we added the full voice chain, and the agent dispatches it autonomously in order: → narration_voice_director: The director-agent reads the seed + story and returns persona_label, search_query, and fallback_query. → voice_sample_builder: Uses yt-dlp + ffmpeg. It accepts a URL, an 11-character ID, or a free-text query. It runs ytsearch5 with dead-video tolerance and normalizes the audio to 24 kHz mono PCM. → voice_clone_synthesize: Wraps ElevenLabs IVC + timestamps. The voice ID is cached by reference SHA. Per-character alignment comes through the same audio call at no extra cost. → voice_clone_cleanup: Frees the cached voice ID after render so orphan voices do not accumulate. ———— 4- Render: Hermes had no built-in video-render entry. So we added the final render tool: → noustiny_storybook: The agent dispatches it as the final step of the chain. One tool call drives the FastAPI render service end to end and emits the mp4. ———— 5- Skills: 13 generic Hermes skills added into skills/creative/: The branching engine in Noustiny works like a council of narrative skills. Each skill is loaded by the gateway as a system prompt and orchestrated in this order: → narrative-brainstorm: Proposes 2 to 3 next-checkpoint options from the canon chain. → narrative-writer-assist: Writes a spliced insert beat that fits the parent and child. → narrative-continuity-critic: Audits downstream beats against the new insert. → narrative-rewriter: Updates the stale beats flagged by the continuity critic. → narrative-judge: Approves or rejects the rewrite against the original flow. → narrative-scene-qa: Checks each beat for consistency, length, and register. → narrative-writer: Finalizes the chosen branch as polished prose. After one splice, this cascade walks downstream by itself until the canon becomes coherent again. ———— 6- Visual + IP pipeline: On the visual side, the goal is not just generating scenes. It is also preserving character continuity and IP safety. This pipeline runs through these skills: → visual-prompt-builder: Turns a beat into an IP-free image prompt and reads the character-sheet references. → scene-composition: Defines shot framing, scene composition, and layout rules. → story-copyright-detector: Skill counterpart of the same-named tool. It can be used for direct slash-command invocation. → character-sheet-builder: Skill counterpart of the same-named tool. Defines cast extraction rules and the IP-free portrait-prompt format used to seed character consistency across the storyboard. → storybook-intro: Generates the cinematic intro page for the render. ———— 7- Voice skill: → narration-voice-director: Defines persona reasoning rules and supports the decision logic behind the same-named voice tool. ———— 8- Pattern: Hermes baseline already had the gateway, agent loop, skill registry, and tool registry. We extended that foundation with 12 generic Hermes tools + 13 generic Hermes skills and organized the system into four main pipelines: • story-state • character continuity • voice • render The important part is this: Noustiny is not a hardcoded system locked inside a single app. A Telegram bot, Discord bot, CLI session, or third-party Next.js app can call the same gateway and use the same tool + skill chains. - No app glue. - No hardcoded prompts. - A drop-in, registry-compatible, agent-native video creation flow. ✅Github:
6:43

Video content creation sounds simple, but what if you don’t have time to: • Write the script, • Prepare the visuals, • Generate the voiceover, • Create the subtitles, • And finally render the video? This is why we built Noustiny on top of Nous Research Hermes Agent by adding 12 generic Hermes tools + 13 generic Hermes skills, bringing the whole process into one single flow. How does it work? Let’s take a closer look 👇 ———— 1- Story state: context, tree, motifs: Hermes had no built-in narrative-state primitive for tracking canon, branching story structure, and recurring motifs. So we added three generic Hermes tools for this: → story_tree_graph: Manages the story tree structure. It handles operations like canon path, descendants, and splice insertion points. → narrative_context_builder: Walks the canon chain and returns the live context every narrative skill should reason against. This includes recent chain, mood, and character state. → motif_tracker: Remembers recurring motifs across the story arc. For example, a sword introduced in beat 2 can reappear meaningfully in later scenes. ———— 2- Character / cast pipeline: Hermes had no built-in primitive for cast extraction or character continuity. So we added a four-tool character pipeline: → story_copyright_detector: Handles IP scrubbing. For example, “Iron Man” is converted into an IP-free character description before the image API ever sees it. → character_sheet_builder: Produces 1 to 4 characters. For each character, it creates an IP-free visual description and a hero-portrait prompt. These portraits become the reference frames used across later storyboard scenes. → character_registry_lookup: Finds a character by name inside the cast sheet and attaches the correct portrait reference to each beat. → character_alias_resolver: Resolves aliases like “Mr. Stark” into the main character name. This way, the same character keeps one portrait reference even if they appear under different names. ———— 3- Voice pipeline: Hermes had no built-in primitive for audio acquisition or voice cloning. So we added the full voice chain, and the agent dispatches it autonomously in order: → narration_voice_director: The director-agent reads the seed + story and returns persona_label, search_query, and fallback_query. → voice_sample_builder: Uses yt-dlp + ffmpeg. It accepts a URL, an 11-character ID, or a free-text query. It runs ytsearch5 with dead-video tolerance and normalizes the audio to 24 kHz mono PCM. → voice_clone_synthesize: Wraps ElevenLabs IVC + timestamps. The voice ID is cached by reference SHA. Per-character alignment comes through the same audio call at no extra cost. → voice_clone_cleanup: Frees the cached voice ID after render so orphan voices do not accumulate. ———— 4- Render: Hermes had no built-in video-render entry. So we added the final render tool: → noustiny_storybook: The agent dispatches it as the final step of the chain. One tool call drives the FastAPI render service end to end and emits the mp4. ———— 5- Skills: 13 generic Hermes skills added into skills/creative/: The branching engine in Noustiny works like a council of narrative skills. Each skill is loaded by the gateway as a system prompt and orchestrated in this order: → narrative-brainstorm: Proposes 2 to 3 next-checkpoint options from the canon chain. → narrative-writer-assist: Writes a spliced insert beat that fits the parent and child. → narrative-continuity-critic: Audits downstream beats against the new insert. → narrative-rewriter: Updates the stale beats flagged by the continuity critic. → narrative-judge: Approves or rejects the rewrite against the original flow. → narrative-scene-qa: Checks each beat for consistency, length, and register. → narrative-writer: Finalizes the chosen branch as polished prose. After one splice, this cascade walks downstream by itself until the canon becomes coherent again. ———— 6- Visual + IP pipeline: On the visual side, the goal is not just generating scenes. It is also preserving character continuity and IP safety. This pipeline runs through these skills: → visual-prompt-builder: Turns a beat into an IP-free image prompt and reads the character-sheet references. → scene-composition: Defines shot framing, scene composition, and layout rules. → story-copyright-detector: Skill counterpart of the same-named tool. It can be used for direct slash-command invocation. → character-sheet-builder: Skill counterpart of the same-named tool. Defines cast extraction rules and the IP-free portrait-prompt format used to seed character consistency across the storyboard. → storybook-intro: Generates the cinematic intro page for the render. ———— 7- Voice skill: → narration-voice-director: Defines persona reasoning rules and supports the decision logic behind the same-named voice tool. ———— 8- Pattern: Hermes baseline already had the gateway, agent loop, skill registry, and tool registry. We extended that foundation with 12 generic Hermes tools + 13 generic Hermes skills and organized the system into four main pipelines: • story-state • character continuity • voice • render The important part is this: Noustiny is not a hardcoded system locked inside a single app. A Telegram bot, Discord bot, CLI session, or third-party Next.js app can call the same gateway and use the same tool + skill chains. - No app glue. - No hardcoded prompts. - A drop-in, registry-compatible, agent-native video creation flow. ✅Github:

Ufuk

28,972 görüntüleme • 5 ay önce

Can your agent finally edit your videos? Yup, it's a repo called video use, by Browser Use. You put the raw footage in a folder. Then Claude Code or Codex edits it. It removes the filler words, cuts the dead space, adds the subtitles, and renders the file. Then it checks its own cut points. Most creators use the same small set of edits in every video. That style stays in your head and in your hands. This repo puts it in a file that an agent can read. People ask for a full YouTube channel on day one. They see bad results, and they stop. Start with one format instead. - One founder loom into a 60 second launch video - 3 clips out of one podcast recording Then make the format a system. Then you operate the system, or you sell it. - Real estate agents need listing videos - Coaches need clips - Agencies need ad variations Manual installation with git clone is possible. For 95% of people, the agent is faster. Here's how i intalled it: - Gave the setup prompt to Claude Code with shell access - Let it read install.md - Installed the repo - Connected FFmpeg - Registered the skill
4:22

Can your agent finally edit your videos? Yup, it's a repo called video use, by Browser Use. You put the raw footage in a folder. Then Claude Code or Codex edits it. It removes the filler words, cuts the dead space, adds the subtitles, and renders the file. Then it checks its own cut points. Most creators use the same small set of edits in every video. That style stays in your head and in your hands. This repo puts it in a file that an agent can read. People ask for a full YouTube channel on day one. They see bad results, and they stop. Start with one format instead. - One founder loom into a 60 second launch video - 3 clips out of one podcast recording Then make the format a system. Then you operate the system, or you sell it. - Real estate agents need listing videos - Coaches need clips - Agencies need ad variations Manual installation with git clone is possible. For 95% of people, the agent is faster. Here's how i intalled it: - Gave the setup prompt to Claude Code with shell access - Let it read install.md - Installed the repo - Connected FFmpeg - Registered the skill

The Startup Ideas Podcast (SIP) 🧃

15,605 görüntüleme • 1 ay önce

HERMES AGENT /LEARN IS ONE OF THE MOST UNDERRATED FEATURE. SHOW IT A WORKFLOW ONCE. IT SAVES THE SKILL. REPEATS IT FOREVER WITHOUT RE-EXPLAINING. you publish a YouTube video: write the title, create the thumbnail, write the description, set tags, schedule it. do it once with Hermes watching. type /learn. Hermes distills that workflow into a reusable skill. next time you say "publish this video," the agent follows the exact same steps. no re-explaining. no missed steps. WHAT YOU CAN TEACH IT: → show it your publishing workflow → /learn → give it an article → /learn → walk it through a client onboarding process → /learn → feed it API documentation → /learn → show it how you process invoices → /learn anything you do more than twice should become a /learn skill. THREE WAYS TO USE /LEARN: from a workflow you walked through: do the task once in chat. then /learn. Hermes extracts the procedure from the conversation. from a directory: /learn ~/docs/youtube-publishing/ reads every file. creates the skill. from a URL: /learn https:// any-documentation-page. com reads the page. distills the skill. the skill saves to ~/.hermes/skills/ with a SKILL.md containing: → when to trigger → step-by-step procedure → pitfalls to avoid → verification steps available as a slash command from that moment. WHY THIS CHANGES DAILY WORK: before /learn: you explain the same process to the agent every time you start a new session. session ends. context lost. start over. after /learn: you explain once. the skill persists. every future session already knows the procedure. the agent follows it without prompting. the boring repetitive tasks you do every week become one-command skills you never think about again. comment LEARN and I'll send you the full guide on turning any workflow into a permanent Hermes skill. full Hermes architecture deep-dive in the article 👇
0:37

HERMES AGENT /LEARN IS ONE OF THE MOST UNDERRATED FEATURE. SHOW IT A WORKFLOW ONCE. IT SAVES THE SKILL. REPEATS IT FOREVER WITHOUT RE-EXPLAINING. you publish a YouTube video: write the title, create the thumbnail, write the description, set tags, schedule it. do it once with Hermes watching. type /learn. Hermes distills that workflow into a reusable skill. next time you say "publish this video," the agent follows the exact same steps. no re-explaining. no missed steps. WHAT YOU CAN TEACH IT: → show it your publishing workflow → /learn → give it an article → /learn → walk it through a client onboarding process → /learn → feed it API documentation → /learn → show it how you process invoices → /learn anything you do more than twice should become a /learn skill. THREE WAYS TO USE /LEARN: from a workflow you walked through: do the task once in chat. then /learn. Hermes extracts the procedure from the conversation. from a directory: /learn ~/docs/youtube-publishing/ reads every file. creates the skill. from a URL: /learn https:// any-documentation-page. com reads the page. distills the skill. the skill saves to ~/.hermes/skills/ with a SKILL.md containing: → when to trigger → step-by-step procedure → pitfalls to avoid → verification steps available as a slash command from that moment. WHY THIS CHANGES DAILY WORK: before /learn: you explain the same process to the agent every time you start a new session. session ends. context lost. start over. after /learn: you explain once. the skill persists. every future session already knows the procedure. the agent follows it without prompting. the boring repetitive tasks you do every week become one-command skills you never think about again. comment LEARN and I'll send you the full guide on turning any workflow into a permanent Hermes skill. full Hermes architecture deep-dive in the article 👇

YanXbt

13,150 görüntüleme • 3 ay önce

We’ve been turning our articles into social-ready videos. Here’s how to do it with HyperFrames: 1. Give Claude the article and ask for an opening hook and a sequence of scenes. Confirm the choices against the piece. 2. Ask for one still image per scene, with the onscreen text, and colors from the cover image. Check the story before approving animation. 3. Have Claude animate the approved storyboard with Hyperframes. For an animated cover, use MiniMax in Flora and give Claude the resulting clip. 4. Watch the preview. Flag unreadable text, cropped letters, or scenes that pass too quickly. Review again after each round of changes. Once the video works, ask Claude to save the process and your corrections as a reusable skill—including the approval steps. For Katie Parrott’s Compound Writing guide, Becky Isjwara made an 18-second video showing flying papers from the cover, followed by the writing process in a loop. Read the full piece:
0:35

We’ve been turning our articles into social-ready videos. Here’s how to do it with HyperFrames: 1. Give Claude the article and ask for an opening hook and a sequence of scenes. Confirm the choices against the piece. 2. Ask for one still image per scene, with the onscreen text, and colors from the cover image. Check the story before approving animation. 3. Have Claude animate the approved storyboard with Hyperframes. For an animated cover, use MiniMax in Flora and give Claude the resulting clip. 4. Watch the preview. Flag unreadable text, cropped letters, or scenes that pass too quickly. Review again after each round of changes. Once the video works, ask Claude to save the process and your corrections as a reusable skill—including the approval steps. For Katie Parrott’s Compound Writing guide, Becky Isjwara made an 18-second video showing flying papers from the cover, followed by the writing process in a loop. Read the full piece:

Every 📧

18,807 görüntüleme • 10 gün önce

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇
26:15

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

YanXbt

32,680 görüntüleme • 4 ay önce

HERMES AGENT TURNS EXPENSE TRACKING INTO ZERO FRICTION. No Siri Shortcuts. No manual entry. Just open Telegram and say: “Hey Bob, I spent $15 on dinner at Guzman Y Gomez.” Done. Hermes profile “Bob” automatically: - Parses the message - Categorizes the expense - Writes directly to your Notion database - Asks clarifying questions when needed (e.g. “Summit” — clothing brand or location?) This is the real advantage of Hermes profiles. You create specialist agents with their own memory, tools, and instructions instead of talking to one generic assistant. Quick setup: 1. Create the profile `hermes profile create bob` 2. Connect Telegram `hermes gateway setup` 3. Equip Bob with tools Enable the Notion integration + required MCP servers so he can write to your database. 4. Define the rules Set categories, formatting and clarification logic in his system prompt or SOUL. md .HERMES AGENT TURNS EXPENSE TRACKING INTO ZERO FRICTION. No Siri Shortcuts. No manual entry. Just open Telegram and say: “Hey Bob, I spent $15 on dinner at Guzman Y Gomez.” Done. Hermes profile “Bob” automatically: - Parses the message - Categorizes the expense - Writes directly to your Notion database - Asks clarifying questions when needed This is the real power of Hermes profiles — you create specialist agents with their own memory, tools, and instructions. Quick setup: 1. Create the profile `hermes profile create bob` 2. Connect Telegram `hermes gateway setup` 3. Equip Bob with tools Enable Notion integration + required MCP servers 4. Set the rules Define categories and logic in his system prompt / SOUL.md The best expense system is the one you actually use every day. Hermes + Telegram removes almost all friction. Want the full ready-to-use setup for your own expense tracker? comment “TELEGRAM” below and I’ll send you the complete configuration. Now you have a real personal finance assistant living in Telegram — always on, zero effort. The best expense system is the one you actually use every day. Hermes + Telegram removes almost all friction. This is how you turn an AI into a daily virtual employee. full guide on building these workflows in the article 👇
1:51

HERMES AGENT TURNS EXPENSE TRACKING INTO ZERO FRICTION. No Siri Shortcuts. No manual entry. Just open Telegram and say: “Hey Bob, I spent $15 on dinner at Guzman Y Gomez.” Done. Hermes profile “Bob” automatically: - Parses the message - Categorizes the expense - Writes directly to your Notion database - Asks clarifying questions when needed (e.g. “Summit” — clothing brand or location?) This is the real advantage of Hermes profiles. You create specialist agents with their own memory, tools, and instructions instead of talking to one generic assistant. Quick setup: 1. Create the profile `hermes profile create bob` 2. Connect Telegram `hermes gateway setup` 3. Equip Bob with tools Enable the Notion integration + required MCP servers so he can write to your database. 4. Define the rules Set categories, formatting and clarification logic in his system prompt or SOUL. md .HERMES AGENT TURNS EXPENSE TRACKING INTO ZERO FRICTION. No Siri Shortcuts. No manual entry. Just open Telegram and say: “Hey Bob, I spent $15 on dinner at Guzman Y Gomez.” Done. Hermes profile “Bob” automatically: - Parses the message - Categorizes the expense - Writes directly to your Notion database - Asks clarifying questions when needed This is the real power of Hermes profiles — you create specialist agents with their own memory, tools, and instructions. Quick setup: 1. Create the profile `hermes profile create bob` 2. Connect Telegram `hermes gateway setup` 3. Equip Bob with tools Enable Notion integration + required MCP servers 4. Set the rules Define categories and logic in his system prompt / SOUL.md The best expense system is the one you actually use every day. Hermes + Telegram removes almost all friction. Want the full ready-to-use setup for your own expense tracker? comment “TELEGRAM” below and I’ll send you the complete configuration. Now you have a real personal finance assistant living in Telegram — always on, zero effort. The best expense system is the one you actually use every day. Hermes + Telegram removes almost all friction. This is how you turn an AI into a daily virtual employee. full guide on building these workflows in the article 👇

YanXbt

21,511 görüntüleme • 4 ay önce

HERMES AGENT + OBSIDIAN IS A COMBINATION NOBODY IS TALKING ABOUT. Hermes ships with a bundled Obsidian skill. read, search, and create notes in your vault out of the box. why this combination is powerful: Hermes built-in memory is capped. MEMORY.md: 2,200 chars (~800 tokens). USER.md: 1,375 chars (~500 tokens). Obsidian vault has no cap. your agent writes research, session summaries, project context, and learned patterns as linked markdown notes. unlimited depth. the agent creates indexed notes by design. timestamps, backlinks, tags. every note connects to the knowledge graph. three ways to integrate: 1. BUNDLED OBSIDIAN SKILL (simplest) ships with Hermes. reads, searches, creates notes in your vault directly. hermes skills list | grep obsidian 2. OBSIDIAN MCP SERVER (deepest) 30+ tools: full-text search, tag lookup, note management, vault analysis, link analysis, orphan detection. add it via: hermes mcp 3. TELEGRAM + CRON → VAULT (always-on) set a cron job that writes daily summaries, research findings, or task reports directly into your Obsidian vault. your agent feeds the vault while you sleep. you review in Obsidian when you're ready. the unlock: Hermes memory handles what the agent needs to know per session (capped, injected). Obsidian handles everything the agent has ever learned (uncapped, searchable). short-term in Hermes. long-term in Obsidian. both accessible. both persistent. keep the vault scope narrow at first. start with one /Hermes folder. expand once you trust the workflow. 8 Loops Indise Hermes Agent👇
0:56

HERMES AGENT + OBSIDIAN IS A COMBINATION NOBODY IS TALKING ABOUT. Hermes ships with a bundled Obsidian skill. read, search, and create notes in your vault out of the box. why this combination is powerful: Hermes built-in memory is capped. MEMORY.md: 2,200 chars (~800 tokens). USER.md: 1,375 chars (~500 tokens). Obsidian vault has no cap. your agent writes research, session summaries, project context, and learned patterns as linked markdown notes. unlimited depth. the agent creates indexed notes by design. timestamps, backlinks, tags. every note connects to the knowledge graph. three ways to integrate: 1. BUNDLED OBSIDIAN SKILL (simplest) ships with Hermes. reads, searches, creates notes in your vault directly. hermes skills list | grep obsidian 2. OBSIDIAN MCP SERVER (deepest) 30+ tools: full-text search, tag lookup, note management, vault analysis, link analysis, orphan detection. add it via: hermes mcp 3. TELEGRAM + CRON → VAULT (always-on) set a cron job that writes daily summaries, research findings, or task reports directly into your Obsidian vault. your agent feeds the vault while you sleep. you review in Obsidian when you're ready. the unlock: Hermes memory handles what the agent needs to know per session (capped, injected). Obsidian handles everything the agent has ever learned (uncapped, searchable). short-term in Hermes. long-term in Obsidian. both accessible. both persistent. keep the vault scope narrow at first. start with one /Hermes folder. expand once you trust the workflow. 8 Loops Indise Hermes Agent👇

YanXbt

20,617 görüntüleme • 4 ay önce

NOTE: read the entire post before commenting. The new xAI video/image API is extremely fast, very cheap, and produces high-quality video. I built an app using the xAI Video API to create newscasts about, xAI, SpaceX, Starlink, Neuralink, X, Grok. Step 1: Grok writes a newscast script from stories gathered around the web. TODO: Notice the inconsistencies in the video. Needs cross-references with the current date. Step 2: Use Grok Imagine Video to generate ~15-second video clips for each segment. Chain these segments by feeding the last frame of each video as the input for the next segment. TODO: Notice in the video that the quality degrades over time. Use the api to upscale each previous frame. Step 3: Export all segments as a single concatenated video. TODO: Notice speaking errors. Split segments into short clips so you can fix them with the video API.
2:30

NOTE: read the entire post before commenting. The new xAI video/image API is extremely fast, very cheap, and produces high-quality video. I built an app using the xAI Video API to create newscasts about, xAI, SpaceX, Starlink, Neuralink, X, Grok. Step 1: Grok writes a newscast script from stories gathered around the web. TODO: Notice the inconsistencies in the video. Needs cross-references with the current date. Step 2: Use Grok Imagine Video to generate ~15-second video clips for each segment. Chain these segments by feeding the last frame of each video as the input for the next segment. TODO: Notice in the video that the quality degrades over time. Use the api to upscale each previous frame. Step 3: Export all segments as a single concatenated video. TODO: Notice speaking errors. Split segments into short clips so you can fix them with the video API.

tetsuo

27,838 görüntüleme • 8 ay önce