self-improve

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Capture durable user feedback into the governing skill/doc, or propose creating a new skill when no suitable one exists, so future sessions don't repeat the mistake. Use when the user rejects, reverts, or overrides the agent's output or approach on something a skill/doc covers or should cover, and when manually invoked to improve or create guidance.

AI & Automation 50 stars 11 forks Updated yesterday MIT

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Skill Content

# Self-improve **Suggest** durable improvements to the skill or governing doc that should have steered the agent, so the next session gets it right without being told again — and apply them only after the user approves. The skill proposes; the user stays in control of every change. Three ways in: - **Manual** — the user invokes `/self-improve` to deliberately improve a skill or doc. - **Self-triggered** — the agent notices it was corrected on something a skill/doc governs (or should). Don't silently correct and move on, but don't derail the task either: note the lesson, finish what the user asked for, and offer to persist it at the next natural breakpoint. - **Driven by another skill** — a caller hands over content that is already durable guidance plus an already-chosen target (scope, form, and path — possibly a new file). It resolved both with the user, so skip steps 1-2 and run only draft + apply. "Skill/doc" means any standing instruction: a `SKILL.md`, `AGENTS.md`/`CLAUDE.md`, a coding-standards or convention doc, a rules file — anything that guides future agents. ## Hard rules - **Confirm before applying.** The skill's job is to **suggest**, never to change text on its own. Never edit a skill or doc without the user's explicit go-ahead on the concrete change — present it as a diff and apply only on approval, whether the user invoked the skill or the agent self-triggered. State plainly whether a change is not yet applied (awaiting approval) or already ...

Details

Author
eai-org
Repository
eai-org/agent-toolkit
Created
4 months ago
Last Updated
yesterday
Language
Shell
License
MIT

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