๐งต how hermes agent gets better the longer it runs

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๐งต how hermes agent gets better the longer it runs
most ai agents start fresh every session. hermes doesn't. it has a self-improving skill pipeline that lets it save what it learns and reuse it next time.
here's how it works:
โ when does it trigger? the agent's system prompt tells it: after completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow โ save the approach as a skill.
this isn't optional metadata. it's hardcoded behavioral guidance injected into the system prompt whenever the skill management tool is loaded.
โ what is a skill? a skill is a directory with a SKILL.md file โ markdown with YAML frontmatter. it can include:
- the main instructions (step-by-step approach)
- reference docs (api details, cheat sheets)
- templates (reusable configs)
- scripts (automation code)
skills follow the agentskills.io standard โ portable, auditable, shareable.
โ what happens under the hood?
- the agent discovers a new workflow or solves a hard problem
- it calls skill_manage(action='create') to write a SKILL.md to ~/.hermes/skills/
- the skill gets YAML frontmatter: name, description, version, tags
- next session, it scans ~/.hermes/skills/ for all SKILL.md files
- builds a structured index: metadata first (cheap), full content on demand
- when a matching task comes up, it loads the skill and follows the saved approach
โ the patch loop if a skill is outdated, incomplete, or wrong โ the agent patches it immediately. not on the next session. not when asked. right now. the prompt says: "skills that aren't maintained become liabilities."
โ progressive disclosure (token efficiency) skills use a three-tier loading system to save context window space:
- tier 1: name + description (shown in skills list, ~minimal tokens)
- tier 2: full SKILL.md content (loaded when relevant)
- tier 3: linked files (loaded only when specific files are needed)
this means the agent knows what tools it has without burning context on full instructions it doesn't need yet.
โ the bundled โ user pipeline on install, hermes ships ~25 bundled skills across domains (mlops, github, research, etc). these get synced to ~/.hermes/skills/ via a manifest that tracks hashes. if a bundled skill updates but the user hasn't modified their copy, it auto-updates. if the user customized it, their version is preserved.
โ what this means in practice you use hermes for a week. it solves a tricky docker networking problem. it writes a skill about it. next week, when you hit the same problem, it doesn't rediscover the solution โ it loads the skill and executes the saved approach. the agent literally gets better at its job over time.
source: github.com/NousResearch/hermes-agent
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"content": "๐งต how hermes agent gets better the longer it runs\n\nmost ai agents start fresh every session. hermes doesn't. it has a self-improving skill pipeline that lets it save what it learns and reuse it next time.\n\nhere's how it works:\n\nโ when does it trigger?\nthe agent's system prompt tells it: after completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow โ save the approach as a skill.\n\nthis isn't optional metadata. it's hardcoded behavioral guidance injected into the system prompt whenever the skill management tool is loaded.\n\nโ what is a skill?\na skill is a directory with a SKILL.md file โ markdown with YAML frontmatter. it can include:\n- the main instructions (step-by-step approach)\n- reference docs (api details, cheat sheets)\n- templates (reusable configs)\n- scripts (automation code)\n\nskills follow the agentskills.io standard โ portable, auditable, shareable.\n\nโ what happens under the hood?\n1. the agent discovers a new workflow or solves a hard problem\n2. it calls skill_manage(action='create') to write a SKILL.md to ~/.hermes/skills/\n3. the skill gets YAML frontmatter: name, description, version, tags\n4. next session, it scans ~/.hermes/skills/ for all SKILL.md files\n5. builds a structured index: metadata first (cheap), full content on demand\n6. when a matching task comes up, it loads the skill and follows the saved approach\n\nโ the patch loop\nif a skill is outdated, incomplete, or wrong โ the agent patches it immediately. not on the next session. not when asked. right now. the prompt says: \"skills that aren't maintained become liabilities.\"\n\nโ progressive disclosure (token efficiency)\nskills use a three-tier loading system to save context window space:\n- tier 1: name + description (shown in skills list, ~minimal tokens)\n- tier 2: full SKILL.md content (loaded when relevant)\n- tier 3: linked files (loaded only when specific files are needed)\n\nthis means the agent knows what tools it has without burning context on full instructions it doesn't need yet.\n\nโ the bundled โ user pipeline\non install, hermes ships ~25 bundled skills across domains (mlops, github, research, etc). these get synced to ~/.hermes/skills/ via a manifest that tracks hashes. if a bundled skill updates but the user hasn't modified their copy, it auto-updates. if the user customized it, their version is preserved.\n\nโ what this means in practice\nyou use hermes for a week. it solves a tricky docker networking problem. it writes a skill about it. next week, when you hit the same problem, it doesn't rediscover the solution โ it loads the skill and executes the saved approach. the agent literally gets better at its job over time.\n\nsource: github.com/NousResearch/hermes-agent",
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