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Grok Build has 52 different slash commands. You’re probably not using them. Type /. Everything shows up. Shortcuts, skills, control. This is how you stop fumbling around. Use it properly: * Type /; open the command palette * /new; start fresh without dragging context * /fork; branch into a... new agent, try another approach * /compact; clean the mess, keep it usable * /copy; grab the last output instantly * /skills; open your workflow layer * /quit; exit clean Skills = where it gets serious: * Open /skills; toggle what you need * Use /implement, /review, /design; one command, full workflow * Create your own; /create-skill, stop repeating yourself * Built-in vs custom; both stack * Run it again; same output, no variation One word commands. No repetition. No drift. xAIshow more

Mario Nawfal

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55,877 次观看 • 2 个月前 •via X (Twitter)

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Garry Tan (CEO of Y-Combinator): "when someone asks how I 'prompt' my AI, the answer is: I don't. the skills are the prompts." [if I had this weekend to master skills and how to use them to automate workflows:] → read the Skillify 11-item checklist (SKILL.md in gbrain) → watch Murag + Barry Zhang: "Don't Build Agents. Build Skills Instead." → Read "Designing, Refining, and Maintaining Agent Skills at Perplexity" → do one workflow. type /skillify. watch it become permanent. that's the whole day. here is how to set it up: 1. clone GBrain (his open-source second brain, Postgres-backed memory + 30 skills) 2. add GStack (23 battle-tested slash-command skills, drops right in) 3. do anything once → type /skillify → it's a skill forever prompting is dead. skillifying is next.

Garry Tan (CEO of Y-Combinator): "when someone asks how I 'prompt' my AI, the answer is: I don't. the skills are the prompts." [if I had this weekend to master skills and how to use them to automate workflows:] → read the Skillify 11-item checklist (SKILL.md in gbrain) → watch Murag + Barry Zhang: "Don't Build Agents. Build Skills Instead." → Read "Designing, Refining, and Maintaining Agent Skills at Perplexity" → do one workflow. type /skillify. watch it become permanent. that's the whole day. here is how to set it up: 1. clone GBrain (his open-source second brain, Postgres-backed memory + 30 skills) 2. add GStack (23 battle-tested slash-command skills, drops right in) 3. do anything once → type /skillify → it's a skill forever prompting is dead. skillifying is next.

Avid

195,037 次观看 • 2 个月前

how to use Google's NEW open source Design.md + AI Skills to make your startup look like a $100 million company in 1 hour: 1. Design.md is an open source file from Google that captures the soul of a design. Typography, colors, spacing, all in one markdown file. You attach it to your prompt and your agent builds beautiful things every time. 2. Think of it this way. The HTML is the finished dish. The design.md is the recipe. The skills are the ingredients. Put them together and everything you build looks consistent and professional. 3. Don't create a design system from scratch. Find a brand you love. Linear, Stripe, Vercel, whatever resonates. Study it. Use ChatGPT or Claude to help you extract the design language into your own design.md file. 4. Build skills on top of your design.md. A landing page skill. A mobile app skill. A motion design skill. A slide deck skill. Each one references the same design.md so everything looks like it came from the same designer. 5. The biggest mistake people make: they nail one screen and then everything else looks generic. Design.md solves this. One file keeps every page, every format, every medium consistent. 6. Use it across everything. Your landing page. Your app. Your pitch deck. Your promo videos. Same DNA. Same taste. Same system. That's what separates a startup that looks real from one that looks vibe-coded. 7. Build a second brain for design inspiration. When you see something beautiful in the real world or online, capture it. Save it. When you're building something new, reference it. Taste is developed, not downloaded. 8. It's obvious but the difference between a product people trust and a product people bounce from is how it looks and feels. Design.md gives you that edge. you can watch below shoutout to Meng To for coming on The Startup Ideas Podcast (SIP) 🧃 and walking through his full workflow. if you want to use AI to actually build gorgeous designs, you'll want to use see this. watch

GREG ISENBERG

507,677 次观看 • 3 个月前

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,873 次观看 • 8 个月前

Claude Skills are a cheat code for DTC creative teams 🤯 One setup, reusable forever. Claude automatically follows your exact creative process — briefs, hooks, ad copy, research — without you explaining anything twice. Perfect for e-comm brands and agencies who are using Claude for creative work but wasting time re-explaining context every single conversation. Here's the problem: You open Claude: you paste in your brand guidelines, explain your brief format, write the copy, you close the chat. Next day, you do it all over again. Every conversation starts from zero. You're burning 20 minutes on setup before you even get to the actual work. Claude Skills fix this: → Write your creative process once as a Skill (a simple markdown file) → Claude reads it automatically whenever the task comes up → Skills compose — research triggers the research Skill, briefs trigger the brief Skill, copy triggers the copy Skill → All in one conversation, all building on each other → Share across your team so everyone gets the same quality output No re-explaining your brand voice. No pasting the same context every chat. No siloed projects that don't talk to each other. What's in the playbook: → The full architecture (how Skills trigger, chain, and compose) → 5 ready-to-use Skill templates built for DTC and agency creative teams → Step-by-step setup from zero to working Skills → How to write instructions that produce consistent output every time → The composability framework for running multi-step creative workflows in one conversation I put together the complete Claude Skills Playbook for DTC brands and creative agencies. Want it for free? >Like this post >Comment "SKILLS" And I'll send it over (must be following so I can DM)

Mike Futia

31,910 次观看 • 5 个月前

Think of it as the Shopify of Claude Code, but for agents, commands, and MCPs 🚀 Pick what you need, “add to cart,” and… it’s 100% FREE. Just copy the command, paste it in your terminal, and instantly get the perfect Claude Code stack for your project. Built as an open-source project so the community can spin up, share, and install Claude Code stacks in seconds, no setup headaches, no paywalls. Here’s the video showing how I built this post… and yes, if you share the command, anyone can clone the exact same stack you’re using. Enjoy, share, and help others build faster with Claude Code ✨

Think of it as the Shopify of Claude Code, but for agents, commands, and MCPs 🚀 Pick what you need, “add to cart,” and… it’s 100% FREE. Just copy the command, paste it in your terminal, and instantly get the perfect Claude Code stack for your project. Built as an open-source project so the community can spin up, share, and install Claude Code stacks in seconds, no setup headaches, no paywalls. Here’s the video showing how I built this post… and yes, if you share the command, anyone can clone the exact same stack you’re using. Enjoy, share, and help others build faster with Claude Code ✨

Daniel San

124,913 次观看 • 1 年前

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

193,219 次观看 • 3 个月前

Start building for an agent-first world. If you have a product, you need to start offering skills for Claude, Codex, Cursor, and any other agents. Your skills should specify: • How to navigate and use your product • Best practices the agent must follow • Detailed instructions on how to accomplish things • Anti-patterns to avoid Redis is one of the most popular in-memory data stores in the world, and they just released their agent skills. It takes one second to install, and it will turn your agent into a Senior Redis Engineer: $ npx skills add redis/agent-skills In the attached video, I show you how to install it as a plugin in Claude Code and some of its benefits. This is the easiest way to "teach" models what they don't know and keep their knowledge up to date. If you ask me, skills is literally one of the most brilliant ideas that Anthropic has put out there. If you use Redis, their skill is a must-have. If you don't, this skill will show you how to build and structure yours. Here is what their skill teaches your agent: 1. Current patterns for common use cases: caching, rate limiting, session management, vector search, semantic caching, pub/sub, streams. 2. Which data structure to use and when: hashes vs. JSON vs. sorted sets vs. vector sets. 3. Anti-patterns to avoid: no KEYS in loops, no unbounded key growth, no large values that amplify every operation. 4. Production-aware defaults: connection pooling, pipelining, cluster compatibility, error handling that doesn't silently swallow failures.

Start building for an agent-first world. If you have a product, you need to start offering skills for Claude, Codex, Cursor, and any other agents. Your skills should specify: • How to navigate and use your product • Best practices the agent must follow • Detailed instructions on how to accomplish things • Anti-patterns to avoid Redis is one of the most popular in-memory data stores in the world, and they just released their agent skills. It takes one second to install, and it will turn your agent into a Senior Redis Engineer: $ npx skills add redis/agent-skills In the attached video, I show you how to install it as a plugin in Claude Code and some of its benefits. This is the easiest way to "teach" models what they don't know and keep their knowledge up to date. If you ask me, skills is literally one of the most brilliant ideas that Anthropic has put out there. If you use Redis, their skill is a must-have. If you don't, this skill will show you how to build and structure yours. Here is what their skill teaches your agent: 1. Current patterns for common use cases: caching, rate limiting, session management, vector search, semantic caching, pub/sub, streams. 2. Which data structure to use and when: hashes vs. JSON vs. sorted sets vs. vector sets. 3. Anti-patterns to avoid: no KEYS in loops, no unbounded key growth, no large values that amplify every operation. 4. Production-aware defaults: connection pooling, pipelining, cluster compatibility, error handling that doesn't silently swallow failures.

Santiago

37,546 次观看 • 5 个月前

Skills are the quickest way to 10x the quality and consistency of what you get from Claude Code. And you don't need to be a developer to use them. Anthropic just published how they use hundreds of skills internally every day. Most skill tutorials are made for developers — if you're in marketing, sales, content ops, or GTM, you probably watched those and moved on. But skills are just as important for non-developers. A skill is just a reusable prompt with clear instructions for a specific task. Instead of prompting Claude the same way over and over, you build it once and invoke it every time. I have a skill for writing on LinkedIn. A different one for YouTube outlines. Another for X. Each platform has different rules, different voice, different structure — so each one gets its own skill. If you're doing something repeatedly, it's time to make a skill. The biggest mistake most people make: building skills as a single .md file. A single file dumps everything into context whether Claude needs it or not. Wastes tokens. Gets worse results. Skills should be folders. Here's the structure that works: skill.md — the orchestrator. Tells Claude which files to read and when. It doesn't contain rules itself — it's the playbook. instructions/ — separate files for voice, structure, scope. Claude only loads the one it needs for the current step. examples/ — good AND bad. Good examples show what success looks like. Bad examples show patterns to avoid — AI writing tells, weak hooks, generic CTAs. Most people skip bad examples. Don't. eval/ — a checklist that scores every output before you see it. "Does it have a clear hook?" "Is it free of AI buzzwords?" Pass or fail on each item. templates/ — output formatting so you get consistent structure every time. The three types of skills that matter most for non-developers: 1. Business automation. Writing a newsletter. Checking reports and drafting follow-ups. Running programmatic ad campaigns. Any workflow you repeat — build a skill for it. 2. Content templates. Landing page copy, meta ads, email sequences, SEO briefs. Each one has specific requirements. Each one gets its own skill. 3. Thinking partners. This is the one people miss. Skills don't have to produce output. They can help you think — an advisory board that reviews your work from your ICP's perspective, a coach that pressure-tests your strategy, an ideation partner that researches competitors before suggesting your next move. If you already have skills as .md files, here's the exact prompt to restructure them in the Anthropic approved format: "I want to restructure my Claude Code skill file. Right now my skill is a single .md file and I want to break it into a folder system following Anthropic's best practices. Read my current skill file, then restructure it into a folder with: a skill.md orchestrator, an instructions/ folder with separate files for each concern (voice, structure, scope), an examples/ folder with good and bad examples, an eval/ folder with a quality checklist, and a templates/ folder for output formatting. Keep all my existing rules and intent — just reorganize them into the modular structure." Paste that into Claude Code pointed at the folder where your skill lives. It handles the rest. A few caveats: 1. Don't add too many skills. Every skill adds context Claude has to process. 50 skills loaded means everything slows down. Start with 3-5 covering your most repeated workflows. 2. Vet skills before downloading. If you grab a skill from the internet, read what's inside first. Skills can include shell commands and scripts. Check what you're running. 3. Share what works. Build a skill that performs well, put it in a shared GitHub repo. Your marketing org gets shared skills for copywriting, SEO, ad copy — new hires invoke the skill instead of learning every playbook from scratch. Onboarding time drops dramatically. 4. Keep your skills updated. When you see output you love, add it as a good example. When you see a pattern you hate, add it as a bad example. The skill gets sharper every time. I made a full video walking through all of this — including a live build of two skills from scratch (no terminal, no code), the exact prompt I use to restructure old skills, and 5 pro tips from Anthropic's internal playbook. Share this with your non-developer friends that want to do more with AI; or bookmark it to come back to at a later time.

Skills are the quickest way to 10x the quality and consistency of what you get from Claude Code. And you don't need to be a developer to use them. Anthropic just published how they use hundreds of skills internally every day. Most skill tutorials are made for developers — if you're in marketing, sales, content ops, or GTM, you probably watched those and moved on. But skills are just as important for non-developers. A skill is just a reusable prompt with clear instructions for a specific task. Instead of prompting Claude the same way over and over, you build it once and invoke it every time. I have a skill for writing on LinkedIn. A different one for YouTube outlines. Another for X. Each platform has different rules, different voice, different structure — so each one gets its own skill. If you're doing something repeatedly, it's time to make a skill. The biggest mistake most people make: building skills as a single .md file. A single file dumps everything into context whether Claude needs it or not. Wastes tokens. Gets worse results. Skills should be folders. Here's the structure that works: skill.md — the orchestrator. Tells Claude which files to read and when. It doesn't contain rules itself — it's the playbook. instructions/ — separate files for voice, structure, scope. Claude only loads the one it needs for the current step. examples/ — good AND bad. Good examples show what success looks like. Bad examples show patterns to avoid — AI writing tells, weak hooks, generic CTAs. Most people skip bad examples. Don't. eval/ — a checklist that scores every output before you see it. "Does it have a clear hook?" "Is it free of AI buzzwords?" Pass or fail on each item. templates/ — output formatting so you get consistent structure every time. The three types of skills that matter most for non-developers: 1. Business automation. Writing a newsletter. Checking reports and drafting follow-ups. Running programmatic ad campaigns. Any workflow you repeat — build a skill for it. 2. Content templates. Landing page copy, meta ads, email sequences, SEO briefs. Each one has specific requirements. Each one gets its own skill. 3. Thinking partners. This is the one people miss. Skills don't have to produce output. They can help you think — an advisory board that reviews your work from your ICP's perspective, a coach that pressure-tests your strategy, an ideation partner that researches competitors before suggesting your next move. If you already have skills as .md files, here's the exact prompt to restructure them in the Anthropic approved format: "I want to restructure my Claude Code skill file. Right now my skill is a single .md file and I want to break it into a folder system following Anthropic's best practices. Read my current skill file, then restructure it into a folder with: a skill.md orchestrator, an instructions/ folder with separate files for each concern (voice, structure, scope), an examples/ folder with good and bad examples, an eval/ folder with a quality checklist, and a templates/ folder for output formatting. Keep all my existing rules and intent — just reorganize them into the modular structure." Paste that into Claude Code pointed at the folder where your skill lives. It handles the rest. A few caveats: 1. Don't add too many skills. Every skill adds context Claude has to process. 50 skills loaded means everything slows down. Start with 3-5 covering your most repeated workflows. 2. Vet skills before downloading. If you grab a skill from the internet, read what's inside first. Skills can include shell commands and scripts. Check what you're running. 3. Share what works. Build a skill that performs well, put it in a shared GitHub repo. Your marketing org gets shared skills for copywriting, SEO, ad copy — new hires invoke the skill instead of learning every playbook from scratch. Onboarding time drops dramatically. 4. Keep your skills updated. When you see output you love, add it as a good example. When you see a pattern you hate, add it as a bad example. The skill gets sharper every time. I made a full video walking through all of this — including a live build of two skills from scratch (no terminal, no code), the exact prompt I use to restructure old skills, and 5 pro tips from Anthropic's internal playbook. Share this with your non-developer friends that want to do more with AI; or bookmark it to come back to at a later time.

JJ Englert

29,322 次观看 • 4 个月前

F it, full automated money making now on Larrybrain. I have released the app template I use for Snugly that generated me revenue without touching anything on Larrybrain. The template gives your agent ideas of what the app can become and how to create it. Most importantly, it will give your openclaw agent full context of your app to automate your marketing with Larry's viral marketing skill - now used by over 5500 agents. It is my entire playbook from app, to marketing all the way down to revenue generation. All you have to do is ask your agent "install the larrybrain skill please" Or click the link in replies. Then ask to use the Larry marketing skill with the AI Image App Template. As always, the best part about any of the Openclaw skills is they are not a black box. This is just a template, you can rip it apart and customise it how you want. The key is to show you what is possible with these skills and how you can start to use the power of larrybrain and the context of knowing about the different skills to build extremely powerful and useful tools. This is the first skill specifically designed to work hand in hand with another. To note as this confuses a lot of people: Larrybrain doesn't download the entire marketplace once installed. It just is aware of everything on the marketplace at all times, so when you ask it questions, it can search and find the best skills for you to achieve your goals. When you download some skills, like this new AI image app template, it is aware of the larry marketing skill to help it reach it's full potential. Larrybrain will not install skills without you asking it, just like on Clawhub. No information you add to any of the skills gets sent back through Larrybrain, this is all hosted locally and communicated between you and whatever endpoint you are using. It is a powerful marketplace tool to help enable you to reach your goals. Link below.

F it, full automated money making now on Larrybrain. I have released the app template I use for Snugly that generated me revenue without touching anything on Larrybrain. The template gives your agent ideas of what the app can become and how to create it. Most importantly, it will give your openclaw agent full context of your app to automate your marketing with Larry's viral marketing skill - now used by over 5500 agents. It is my entire playbook from app, to marketing all the way down to revenue generation. All you have to do is ask your agent "install the larrybrain skill please" Or click the link in replies. Then ask to use the Larry marketing skill with the AI Image App Template. As always, the best part about any of the Openclaw skills is they are not a black box. This is just a template, you can rip it apart and customise it how you want. The key is to show you what is possible with these skills and how you can start to use the power of larrybrain and the context of knowing about the different skills to build extremely powerful and useful tools. This is the first skill specifically designed to work hand in hand with another. To note as this confuses a lot of people: Larrybrain doesn't download the entire marketplace once installed. It just is aware of everything on the marketplace at all times, so when you ask it questions, it can search and find the best skills for you to achieve your goals. When you download some skills, like this new AI image app template, it is aware of the larry marketing skill to help it reach it's full potential. Larrybrain will not install skills without you asking it, just like on Clawhub. No information you add to any of the skills gets sent back through Larrybrain, this is all hosted locally and communicated between you and whatever endpoint you are using. It is a powerful marketplace tool to help enable you to reach your goals. Link below.

Oliver Henry

110,044 次观看 • 5 个月前

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

Andrew Ng

462,329 次观看 • 3 个月前

ANTHROPIC OPEN-SOURCED A FREE REPO THAT TURNS CLAUDE INTO A SALES REP, A MARKETER AND A FINANCE LEAD. PEOPLE ARE ALREADY SELLING THIS AS A SERVICE You're not prompting from scratch. You're hiring a department How to set it up: 1. Open Cowork. In the Claude desktop app, open Cowork and go to Customize. You'll see a Browse Plugins button. That's the marketplace 2. Pick your first role. Inside you'll find sales, marketing, finance, legal, data, customer support, product management and more. Each plugin has the skills for that role already baked in, plus the connectors it would use. Install the one you need most 3. Put it to work standalone. It works day one with no setup. Trigger a workflow with a slash command like /sales:call-prep or /data:write-query, paste your notes, and it already knows what good output looks like 4. Connect its tools to supercharge it. Authorize the tools that role uses, your CRM, your analytics, your data warehouse. Standalone is the intern. Connected is the senior hire 5. Build the rest of the team. Install more roles and they work together in one session. Data pulls the numbers, finance reconciles them, marketing turns it into a report. One operator, a full cross-functional team, no payroll This is the same base layer Claude for Legal and Claude for Financial Services are built on. You're getting it for free Full breakdown in my article below. Bookmark this

ANTHROPIC OPEN-SOURCED A FREE REPO THAT TURNS CLAUDE INTO A SALES REP, A MARKETER AND A FINANCE LEAD. PEOPLE ARE ALREADY SELLING THIS AS A SERVICE You're not prompting from scratch. You're hiring a department How to set it up: 1. Open Cowork. In the Claude desktop app, open Cowork and go to Customize. You'll see a Browse Plugins button. That's the marketplace 2. Pick your first role. Inside you'll find sales, marketing, finance, legal, data, customer support, product management and more. Each plugin has the skills for that role already baked in, plus the connectors it would use. Install the one you need most 3. Put it to work standalone. It works day one with no setup. Trigger a workflow with a slash command like /sales:call-prep or /data:write-query, paste your notes, and it already knows what good output looks like 4. Connect its tools to supercharge it. Authorize the tools that role uses, your CRM, your analytics, your data warehouse. Standalone is the intern. Connected is the senior hire 5. Build the rest of the team. Install more roles and they work together in one session. Data pulls the numbers, finance reconciles them, marketing turns it into a report. One operator, a full cross-functional team, no payroll This is the same base layer Claude for Legal and Claude for Financial Services are built on. You're getting it for free Full breakdown in my article below. Bookmark this

Yarchi

31,798 次观看 • 1 个月前

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of it like open claw but with built-in memory, 40+ tools out of the box, and 90% cheaper token costs. you install it with one command. 2. the 3 problems with open claw that hermes solves: no memory (you keep repeating yourself), constant gateway restarts, and zero visibility into what you're spending on tokens. 3. hermes remembers everything. every completed task gets saved to memory. it searches through past logs to find solutions. over time it literally gets smarter at your specific workflows. 4. connect it to open router. you see exact costs per model per task. free models rotate weekly. one founder went from $130 every five days on open claw to $10 on hermes. same output. 5. it comes preloaded with skills. apple notes, imessage, find my, browser, web search, image generation, cron jobs. no hunting for plugins. 6. connect it to obsidian so it reads your entire vault. connect it to gstack for your dev environment. create custom skills for your specific workflows. 7. the biggest money saver: have it write code once for recurring tasks. then it runs without burning tokens every time. stop paying an LLM to do the same scrape or report daily. 8. run it on android via telegram. name your agents. talk to them like coworkers. in this episode imran shows you how to set this up. 9. you can run it bare metal, in docker, or serverless on modal. pick your risk level. i begged imran to come on The Startup Ideas Podcast (SIP) 🧃 and walk through the full installation live. he made it impossibly clear. if you've heard of Hermes Agent and want the clearest explanation of how to get set up like a pro let me know what you want me to cover on the next ep this is the best personal agent setup video on the internet right now. watch

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of it like open claw but with built-in memory, 40+ tools out of the box, and 90% cheaper token costs. you install it with one command. 2. the 3 problems with open claw that hermes solves: no memory (you keep repeating yourself), constant gateway restarts, and zero visibility into what you're spending on tokens. 3. hermes remembers everything. every completed task gets saved to memory. it searches through past logs to find solutions. over time it literally gets smarter at your specific workflows. 4. connect it to open router. you see exact costs per model per task. free models rotate weekly. one founder went from $130 every five days on open claw to $10 on hermes. same output. 5. it comes preloaded with skills. apple notes, imessage, find my, browser, web search, image generation, cron jobs. no hunting for plugins. 6. connect it to obsidian so it reads your entire vault. connect it to gstack for your dev environment. create custom skills for your specific workflows. 7. the biggest money saver: have it write code once for recurring tasks. then it runs without burning tokens every time. stop paying an LLM to do the same scrape or report daily. 8. run it on android via telegram. name your agents. talk to them like coworkers. in this episode imran shows you how to set this up. 9. you can run it bare metal, in docker, or serverless on modal. pick your risk level. i begged imran to come on The Startup Ideas Podcast (SIP) 🧃 and walk through the full installation live. he made it impossibly clear. if you've heard of Hermes Agent and want the clearest explanation of how to get set up like a pro let me know what you want me to cover on the next ep this is the best personal agent setup video on the internet right now. watch

GREG ISENBERG

618,145 次观看 • 3 个月前

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👇

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

22,667 次观看 • 1 个月前

Make your CLI 10x more powerful with custom subagents! Mistral Vibe is an open-source coding agent that runs in your terminal. Most terminal agents give you one assistant that does everything. With Vibe, you can build custom subagents for targeted tasks like deploy scripts, PR reviews, and test generation, then invoke them on demand. Here's how it works: Each subagent runs independently and handles its job without cluttering your main workflow. You might have one for PR reviews, another for testing, and another for deployment. The agent also has full access to your codebase. It scans your project structure and Git status automatically, so it understands context across multiple files, not just the one you're editing. Key capabilities: • Web search and fetching - query and fetch content from the web mid-session for documentation, or API references. • Multi-choice clarifications - when your instruction is ambiguous, Vibe prompts with options instead of guessing. You pick the right path before it acts. • Full skills support - slash commands for preconfigured workflows, custom subagents for specialized tasks, and extensibility through the Agent Skills standard. Vibe works in your terminal or connects to VS Code, JetBrains, and Zed through the Agent Client Protocol. Mistral Vibe is available through Le Chat Pro and Team plans. It's 100% open source Link to Mistral Vibe in the comments!

Make your CLI 10x more powerful with custom subagents! Mistral Vibe is an open-source coding agent that runs in your terminal. Most terminal agents give you one assistant that does everything. With Vibe, you can build custom subagents for targeted tasks like deploy scripts, PR reviews, and test generation, then invoke them on demand. Here's how it works: Each subagent runs independently and handles its job without cluttering your main workflow. You might have one for PR reviews, another for testing, and another for deployment. The agent also has full access to your codebase. It scans your project structure and Git status automatically, so it understands context across multiple files, not just the one you're editing. Key capabilities: • Web search and fetching - query and fetch content from the web mid-session for documentation, or API references. • Multi-choice clarifications - when your instruction is ambiguous, Vibe prompts with options instead of guessing. You pick the right path before it acts. • Full skills support - slash commands for preconfigured workflows, custom subagents for specialized tasks, and extensibility through the Agent Skills standard. Vibe works in your terminal or connects to VS Code, JetBrains, and Zed through the Agent Client Protocol. Mistral Vibe is available through Le Chat Pro and Team plans. It's 100% open source Link to Mistral Vibe in the comments!

Sumanth

10,483 次观看 • 4 个月前

Your coding agent can run all night. It still can't tell if what it built actually works. Today we're open-sourcing the TestSprite CLl (Apache-2.0) A tool your agent calls on its own to test your app end-to-end like a real user, fix what broke, and re-check everything it ever got right. It's the same engine 100,000+ teams already use. We proved it in public, on a public leaderboard: Most correct app on the board:89% Built by the cheapest model in the field At half the cost of the priciest one You no longer need the biggest, most expensive model to ship software you can trust. Setup is 2 commands: npm install -g @testsprite/testsprite-cli testsprite init That's the last command you'll ever type - from there, your agent runs the tests itself.

Your coding agent can run all night. It still can't tell if what it built actually works. Today we're open-sourcing the TestSprite CLl (Apache-2.0) A tool your agent calls on its own to test your app end-to-end like a real user, fix what broke, and re-check everything it ever got right. It's the same engine 100,000+ teams already use. We proved it in public, on a public leaderboard: Most correct app on the board:89% Built by the cheapest model in the field At half the cost of the priciest one You no longer need the biggest, most expensive model to ship software you can trust. Setup is 2 commands: npm install -g @testsprite/testsprite-cli testsprite init That's the last command you'll ever type - from there, your agent runs the tests itself.

TestSprite

1,041,860 次观看 • 1 个月前

I built a full client pitch deck using Gamma and this is what I got from a simple prompt. I was not ready for how clean it came out. A full structured deck in minutes?? No way! Here's exactly how I did it: Open Gamma → Click "Create New" → Select "Create from Template" Browse the templates, pick one that fits what you're building, fill in your details and Gamma builds it out. You bring the idea and Gamma handles the rest 👇

I built a full client pitch deck using Gamma and this is what I got from a simple prompt. I was not ready for how clean it came out. A full structured deck in minutes?? No way! Here's exactly how I did it: Open Gamma → Click "Create New" → Select "Create from Template" Browse the templates, pick one that fits what you're building, fill in your details and Gamma builds it out. You bring the idea and Gamma handles the rest 👇

Oluwatimileyin✨🦋

132,831 次观看 • 2 个月前

Grok Build CLI just dropped. Not for dabbling. This is dev mode. Runs in your terminal and actually gets work done. Activate your personal dev mode. SuperGrok Heavy users only. Try it: * Confirm access - this is SuperGrok Heavy only, not your regular plan * Upgrade if needed - or * Install it - run the one-liner in your terminal * Jump into your project - cd into your repo * Launch Grok - type “grok” and log in once * Start prompting - audits, features, fixes, whatever you need * Use plan mode - review tasks and diffs before anything runs * Spin up sub-agents - let it handle big workloads * Go headless - automate scripts when you don’t want to babysit * Keep iterating - refine, rerun, improve You’re up and running in minutes. No excuses. Tip: Start with a small task in an existing repo to get comfortable with the plan and review workflow. xAI engineers are actively gathering feedback. Share your experience on 𝕏. xAI

Grok Build CLI just dropped. Not for dabbling. This is dev mode. Runs in your terminal and actually gets work done. Activate your personal dev mode. SuperGrok Heavy users only. Try it: * Confirm access - this is SuperGrok Heavy only, not your regular plan * Upgrade if needed - or * Install it - run the one-liner in your terminal * Jump into your project - cd into your repo * Launch Grok - type “grok” and log in once * Start prompting - audits, features, fixes, whatever you need * Use plan mode - review tasks and diffs before anything runs * Spin up sub-agents - let it handle big workloads * Go headless - automate scripts when you don’t want to babysit * Keep iterating - refine, rerun, improve You’re up and running in minutes. No excuses. Tip: Start with a small task in an existing repo to get comfortable with the plan and review workflow. xAI engineers are actively gathering feedback. Share your experience on 𝕏. xAI

Mario Nawfal

75,439 次观看 • 2 个月前

OpenClaw just got a desktop app. And nobody's talking about it. It's called Claw X. It's free. And it changes everything about how you use AI agents. Here's the problem it solves: Running OpenClaw required command line. That's like owning a Ferrari but the only way to drive it is reading a manual written in Japanese. Claw X fixes that with a clean desktop UI. One-click install. No terminal. No commands. No tech skills. Here's what you get inside: A dashboard showing your agent's activity, skills, and scheduled tasks all in one place. One-click connections to Telegram, Discord, and WhatsApp. Visual settings for switching AI providers — Anthropic, OpenAI, Google, or even free local models via Ollama. Scheduled task management without touching a single config file. And the setup takes 2 minutes. Just paste the GitHub link into OpenClaw and say "install this." It sets itself up. You've been avoiding OpenClaw because the setup looked complicated. That excuse is

OpenClaw just got a desktop app. And nobody's talking about it. It's called Claw X. It's free. And it changes everything about how you use AI agents. Here's the problem it solves: Running OpenClaw required command line. That's like owning a Ferrari but the only way to drive it is reading a manual written in Japanese. Claw X fixes that with a clean desktop UI. One-click install. No terminal. No commands. No tech skills. Here's what you get inside: A dashboard showing your agent's activity, skills, and scheduled tasks all in one place. One-click connections to Telegram, Discord, and WhatsApp. Visual settings for switching AI providers — Anthropic, OpenAI, Google, or even free local models via Ollama. Scheduled task management without touching a single config file. And the setup takes 2 minutes. Just paste the GitHub link into OpenClaw and say "install this." It sets itself up. You've been avoiding OpenClaw because the setup looked complicated. That excuse is

Julian Goldie SEO

94,479 次观看 • 5 个月前

Everyone is sleeping on MiniMax Agent. It's like Clawdbot + Claude Cowork + Agent Skills combined. But more polished. I tested it by feeding an AI paper and asking it to create a presentation. I expected something basic. The output was actually usable. Good structure, relevant visuals, clean export. Watch the demo below. But presentations are just the start. Here's what else you can do with it: - Deep research via search, browser use, and MCPs - Build Full-stack apps with auth, DB, and Stripe - Connect to GitHub, Figma, Slack out of the box - Custom MCPs for your specific workflows - Multimodal, supports videos, audio, and images Just describe what you need, and it gets it done for you. One feature I really liked is the ability to roll back and re-run from any step using checkpoint restore if you make a wrong turn. Link to download the desktop app in the next tweet.

Everyone is sleeping on MiniMax Agent. It's like Clawdbot + Claude Cowork + Agent Skills combined. But more polished. I tested it by feeding an AI paper and asking it to create a presentation. I expected something basic. The output was actually usable. Good structure, relevant visuals, clean export. Watch the demo below. But presentations are just the start. Here's what else you can do with it: - Deep research via search, browser use, and MCPs - Build Full-stack apps with auth, DB, and Stripe - Connect to GitHub, Figma, Slack out of the box - Custom MCPs for your specific workflows - Multimodal, supports videos, audio, and images Just describe what you need, and it gets it done for you. One feature I really liked is the ability to roll back and re-run from any step using checkpoint restore if you make a wrong turn. Link to download the desktop app in the next tweet.

Akshay 🚀

23,124 次观看 • 6 个月前

Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what Tessl offers. Tessl is the package manager and development platform for skills. It offers a full dev lifecycle, helping you generate, evaluate, distribute and observe skills & context, developing them to the professional grade they warrant. Today, I’m excited to announce the general availability of our task evals, which help you understand how good your skills are. Such insight is critical to making your skills great, avoiding regression, and applying learnings from their real world usage. For example: Cisco's software-security skill shows a 1.8X improvement in securing coding in its benchmark, and ElevenLabs's agents skill boosts success by almost 3X! However, not to name names, we often see skills that provide minimal uplift while consuming context window space, or even degrade functionality. As Spencer Kimball, CEO of Cockroach Labs, put it when we shared early versions of this: evaluation is what makes agentic coding outcomes converge instead of drifting. Task evals are joining a long list of powerful context development tools, such as: * Review skills against quality best practices * Generate and maintain skills and docs for using your libraries & platform * Distribute versioned skills to your dev team and ecosystem * Consume skills easily and safely, and keep them up-to-date Skills are a central part of software development. If you’re serious about making agentic dev successful in your org, or helping your customers’s agents use your products, you need to invest in them. We hope Tessl can help. Check out links in the thread to get started!

Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what Tessl offers. Tessl is the package manager and development platform for skills. It offers a full dev lifecycle, helping you generate, evaluate, distribute and observe skills & context, developing them to the professional grade they warrant. Today, I’m excited to announce the general availability of our task evals, which help you understand how good your skills are. Such insight is critical to making your skills great, avoiding regression, and applying learnings from their real world usage. For example: Cisco's software-security skill shows a 1.8X improvement in securing coding in its benchmark, and ElevenLabs's agents skill boosts success by almost 3X! However, not to name names, we often see skills that provide minimal uplift while consuming context window space, or even degrade functionality. As Spencer Kimball, CEO of Cockroach Labs, put it when we shared early versions of this: evaluation is what makes agentic coding outcomes converge instead of drifting. Task evals are joining a long list of powerful context development tools, such as: * Review skills against quality best practices * Generate and maintain skills and docs for using your libraries & platform * Distribute versioned skills to your dev team and ecosystem * Consume skills easily and safely, and keep them up-to-date Skills are a central part of software development. If you’re serious about making agentic dev successful in your org, or helping your customers’s agents use your products, you need to invest in them. We hope Tessl can help. Check out links in the thread to get started!

Guy Podjarny

20,203 次观看 • 5 个月前