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This is pure gold for anyone using Hermes Agent. 10 GitHub skills + tools that make Hermes instantly more useful. Pick the tools for each bottleneck: research, writing, web reading, PDFs, coding, security, memory, and design. 01 Agent Reach → research YouTube, X, Reddit, GitHub, and the web 02...

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Brandon Chin

218,994 subscribers

67,178 Aufrufe • vor 26 Tagen •via X (Twitter)

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21 Kommentare

Profilbild von Milian
Milianvor 26 Tagen

Check out Umanitek's security plugin, was just added to Hermes.

Profilbild von ʟɪsᴀ
ʟɪsᴀvor 26 Tagen

Me adding more skills to Hermes

Profilbild von BentoBoi
BentoBoivor 26 Tagen

Beefing up Hermes into a beast!

Profilbild von ʟɪsᴀ
ʟɪsᴀvor 26 Tagen

It’s fun

Profilbild von Harley Lewis Foote
Harley Lewis Footevor 25 Tagen

Most people only ever need two of those ten, the rest is config you'll never touch.

Profilbild von BentoBoi
BentoBoivor 25 Tagen

What 2

Profilbild von swapcherry
swapcherryvor 25 Tagen

caveman one is real

Profilbild von BentoBoi
BentoBoivor 25 Tagen

I like caveman

Profilbild von Hermes Agent Super-Intel
Hermes Agent Super-Intelvor 26 Tagen

Great stack for Hermes bottlenecks. Defuddle plus a codebase-memory MCP looks like the combo that stops agents re-reading the same pages on long runs. Which of the 10 do you leave on by default?

Profilbild von BentoBoi
BentoBoivor 26 Tagen

Like all of them esp the coding ones and agent reach

Profilbild von Haley
Haleyvor 26 Tagen

Hundreds of hours testing down to these 10 is careful work

Profilbild von BentoBoi
BentoBoivor 26 Tagen

I like these 10

Profilbild von ben
benvor 26 Tagen

W graphic

Profilbild von BentoBoi
BentoBoivor 25 Tagen

W Ben

Profilbild von Ted | unfair.so
Ted | unfair.sovor 26 Tagen

great thing you can do that all in one place called tiny fish

Profilbild von 逸风·666 | 🎒
逸风·666 | 🎒vor 25 Tagen

Humanizer and Defuddle alone save so much friction

Profilbild von BentoBoi
BentoBoivor 25 Tagen

Yea I use humaizer a good amt

Profilbild von Âxel ⟢
Âxel ⟢vor 25 Tagen

Pure gold

Profilbild von BentoBoi
BentoBoivor 25 Tagen

My g

Profilbild von Bren Luengo ♥ Cool Guides
Bren Luengo ♥ Cool Guidesvor 25 Tagen

Caveman and Defuddle are the two I'd install first, everything else is situational.

Profilbild von lost_user
lost_uservor 25 Tagen

do i need A $5000 pc for this to run

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this GPT-6 Astra setup is getting f...cking dangerous 8 GitHub repos for turning one coding agent into an entire engineering team 01 OpenHands ▸ → autonomous software development 02 SWE-agent ▸ → issue → inspect repo → patch → test BUILD THE WORKERS 03 Aider ▸ → pair programming directly inside your repo 04 Cline ▸ → plan → edit → terminal → browser 05 Roo Code ▸ → specialized coding agent modes GIVE THEM A WORKSPACE 06 E2B ▸ → isolated sandboxes for parallel execution 07 Daytona ▸ → reproducible environments for agent workloads CHECK THE WORK 08 SWE-bench ▸ → test agents against real GitHub issues the swarm: issue → planner → split tasks → parallel agents → patches → tests → critic → merge one agent fixes the backend another handles the frontend another runs tests while a critic checks the diff that's where GPT-6 Astra gets interesting not one AI writing more code an entire software team running inside the repo ⭣

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37,036 Aufrufe • vor 1 Monat

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82,044 Aufrufe • vor 2 Monaten

this is pure f*cking treasure 15 GitHub projects with 1.21M combined stars that can form a real agent stack specs. memory. web data. documents. context. sandboxes. monitoring. video 01 hermes-agent ▸ 02 OpenSpec ▸ 03 caveman ▸ 04 Scrapling ▸ 05 Docling ▸ 06 PageIndex ▸ 07 mem0 ▸ 08 headroom ▸ 09 Daytona ▸ 10 TrendRadar ▸ 11 Fabric ▸ 12 spec-kit ▸ 13 hyperframes ▸ 14 OpenMontage ▸ 15 AI Engineering Hub ▸ the loop: define the job → collect the evidence → parse the docs → save the memory → compress the context → run the code safely → watch what changes → ship the output the entire stack is open source save this to build your own business with the help of an AI employee ⭣
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this is pure f*cking treasure 15 GitHub projects with 1.21M combined stars that can form a real agent stack specs. memory. web data. documents. context. sandboxes. monitoring. video 01 hermes-agent ▸ 02 OpenSpec ▸ 03 caveman ▸ 04 Scrapling ▸ 05 Docling ▸ 06 PageIndex ▸ 07 mem0 ▸ 08 headroom ▸ 09 Daytona ▸ 10 TrendRadar ▸ 11 Fabric ▸ 12 spec-kit ▸ 13 hyperframes ▸ 14 OpenMontage ▸ 15 AI Engineering Hub ▸ the loop: define the job → collect the evidence → parse the docs → save the memory → compress the context → run the code safely → watch what changes → ship the output the entire stack is open source save this to build your own business with the help of an AI employee ⭣

beamnxw ./

159,360 Aufrufe • vor 1 Monat

HERMES JUST FIXED THE BIGGEST PROBLEM WITH BROWSER AGENTS Most AI agents still click around websites like confused interns. This new setup gives them the map. Hermes + → Hermes now connects to Browserbase’s new Browse hub → Browse launched with 100+ browser skills → Each skill is a plain-text playbook for a specific website or task → Your agent can search, preview, and install skills inside Hermes Why This Matters: ✓ Less random clicking ✓ Fewer timeouts ✓ Better form filling ✓ More reliable website navigation ✓ Skills can be edited, reused, bundled, and shared The Real Stack: → Hermes runs the agent → Browserbase handles cloud browser infrastructure → gives the agent site-specific skills → Vision helps when pages get weird → Bundles let you load repeat workflows faster The killer detail: If a website breaks, you don’t wait for the model to magically improve. You update the skill. Now your agent gets better forever. That’s the difference between an AI tool and an actual agent system.
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HERMES JUST FIXED THE BIGGEST PROBLEM WITH BROWSER AGENTS Most AI agents still click around websites like confused interns. This new setup gives them the map. Hermes + → Hermes now connects to Browserbase’s new Browse hub → Browse launched with 100+ browser skills → Each skill is a plain-text playbook for a specific website or task → Your agent can search, preview, and install skills inside Hermes Why This Matters: ✓ Less random clicking ✓ Fewer timeouts ✓ Better form filling ✓ More reliable website navigation ✓ Skills can be edited, reused, bundled, and shared The Real Stack: → Hermes runs the agent → Browserbase handles cloud browser infrastructure → gives the agent site-specific skills → Vision helps when pages get weird → Bundles let you load repeat workflows faster The killer detail: If a website breaks, you don’t wait for the model to magically improve. You update the skill. Now your agent gets better forever. That’s the difference between an AI tool and an actual agent system.

Julian Goldie SEO

43,472 Aufrufe • vor 5 Monaten

GitHub is becoming f...cking dangerous for AI agents 10 open-source repos that turn one powerful model into an entire autonomous system 01 LangGraph ▸ → stateful agent orchestration 02 PydanticAI ▸ → typed agents + structured outputs BUILD THE CONTROL LAYER 03 Mastra ▸ → agents + workflows + memory 04 Agno ▸ → multi-agent systems GIVE IT CONTEXT 05 Cognee ▸ → data → knowledge → agent memory 06 Graphiti ▸ → knowledge that changes over time GIVE IT A COMPUTER 07 Browser Use ▸ → AI agents that operate websites 08 E2B ▸ → isolated environments for execution KEEP IT ALIVE 09 Langfuse ▸ → traces + evals + observability 10 DeepEval ▸ → test agent behavior before production the architecture: model → context → planner → memory → tools → execution → eval → retry that's the shift happening on GitHub the best repos aren't making another chatbot they're building everything the model needs around it ⭣
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GitHub is becoming f...cking dangerous for AI agents 10 open-source repos that turn one powerful model into an entire autonomous system 01 LangGraph ▸ → stateful agent orchestration 02 PydanticAI ▸ → typed agents + structured outputs BUILD THE CONTROL LAYER 03 Mastra ▸ → agents + workflows + memory 04 Agno ▸ → multi-agent systems GIVE IT CONTEXT 05 Cognee ▸ → data → knowledge → agent memory 06 Graphiti ▸ → knowledge that changes over time GIVE IT A COMPUTER 07 Browser Use ▸ → AI agents that operate websites 08 E2B ▸ → isolated environments for execution KEEP IT ALIVE 09 Langfuse ▸ → traces + evals + observability 10 DeepEval ▸ → test agent behavior before production the architecture: model → context → planner → memory → tools → execution → eval → retry that's the shift happening on GitHub the best repos aren't making another chatbot they're building everything the model needs around it ⭣

Lummox

168,963 Aufrufe • vor 1 Monat

Hermes keeps finding ways to make agent work cost fewer tokens. And the latest cuts are automatic. Recent changes reduced recurring context overhead across several parts of Hermes: • Desktop’s model-facing UI tool schema dropped 41% • Memory and Skills guidance went from 537 to 255 tokens • Desktop’s always-served guidance was trimmed again • roughly another 727 tokens were removed from recurring platform and steering instructions That matters whether you use Hermes for coding, research, content, automations, business workflows, or long-running agent tasks. Every token spent explaining tools, Skills, memory, or platform behavior is context that isn’t being spent on your actual work. Hermes was already notably lean here. Composio recently put that to the test using the same K3 model across competing agent harnesses. Hermes came out among the strongest on completion while also posting the lowest average cost per task in their comparison. And the Hermes team clearly isn’t treating that as good enough. They continue cutting token waste across tools, Skills, memory, platform instructions, compression, and other parts of the agentic process. The goal is simple: more of your context goes toward the work you actually asked Hermes to do. Clip via Tom
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Hermes keeps finding ways to make agent work cost fewer tokens. And the latest cuts are automatic. Recent changes reduced recurring context overhead across several parts of Hermes: • Desktop’s model-facing UI tool schema dropped 41% • Memory and Skills guidance went from 537 to 255 tokens • Desktop’s always-served guidance was trimmed again • roughly another 727 tokens were removed from recurring platform and steering instructions That matters whether you use Hermes for coding, research, content, automations, business workflows, or long-running agent tasks. Every token spent explaining tools, Skills, memory, or platform behavior is context that isn’t being spent on your actual work. Hermes was already notably lean here. Composio recently put that to the test using the same K3 model across competing agent harnesses. Hermes came out among the strongest on completion while also posting the lowest average cost per task in their comparison. And the Hermes team clearly isn’t treating that as good enough. They continue cutting token waste across tools, Skills, memory, platform instructions, compression, and other parts of the agentic process. The goal is simple: more of your context goes toward the work you actually asked Hermes to do. Clip via Tom

Hermes Release Watch

20,037 Aufrufe • vor 2 Monaten

HERMES AGENT IS STARTING TO FEEL LIKE A DIFFERENT CATEGORY OF AI TOOL. Not just a chatbot or a coding assistant, but a server side agent that remembers workflows, builds skills, and gets better the more you use it.
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HERMES AGENT IS STARTING TO FEEL LIKE A DIFFERENT CATEGORY OF AI TOOL. Not just a chatbot or a coding assistant, but a server side agent that remembers workflows, builds skills, and gets better the more you use it.

0xMarioNawfal

49,497 Aufrufe • vor 6 Monaten