agentify-project
Make a project agent-ready by converging it toward a canonical agent-neutral structure. Re-runnable, and doubles as an audit.
Capture durable user feedback into the governing skill, doc or check, 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,
Claude Code
$ npx -y skills add eai-org/agent-toolkit --skill self-improve --agent claude-code
Codex
$ npx skills add eai-org/agent-toolkit --skill self-improve -a codex -y
Cursor
$ npx skills add eai-org/agent-toolkit --skill self-improve -a cursor -y
Gemini CLI
$ npx skills add eai-org/agent-toolkit --skill self-improve -a gemini-cli -y
GitHub Copilot
$ npx skills add eai-org/agent-toolkit --skill self-improve -a github-copilot -y
OpenCode
$ npx skills add eai-org/agent-toolkit --skill self-improve -a opencode -y
Windsurf
$ npx skills add eai-org/agent-toolkit --skill self-improve -a windsurf -y
name: self-improve description: Capture durable user feedback into the governing skill, doc or check, 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 or check covers or should cover, and when manually invoked to improve or create guidance. allowed-tools: Read, Write, Edit, Glob, Grep, Bash license: MIT metadata: version: "1.13"
**Suggest** durable improvements to the skill, doc or check 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:
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.
lessons already phrased as durable guidance, sometimes with all or part of a target it settled with the user (scope, form, path — possibly a new file or a merge into an existing one). Skip step 1; skip step 2 for a lesson whose target the caller settled fully, run it for the rest keeping what the caller settled — its Mechanical lesson bullet and new-doc indexing requirement always apply. Several lessons at once → first propose their placement as one table, each lesson with its doc, existing or new; then draft + apply, lessons sharing a target as one diff.
"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. A "check" (lint rule, hook, CI job) enforces one mechanically and is not a skill/doc.
Never edit a skill, doc or check 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 applied (and where), so the user never has to ask.
never edit it directly.** A `SKILL.md` goes through [compact-skill-creator](../compact-skill-creator/SKILL.md); any other doc (rule, `AGENTS.md`/`CLAUDE.md`, convention doc) goes through [compact-docs-writer](../compact-docs-writer/SKILL.md). Actually invoke the skill and follow its workflow *before* drafting or applying; reading it, applying its principles by hand, or naming it after a direct edit does not count. A check is edited directly.
Signals the agent was corrected in a way worth persisting: the user rejects or reverts a choice ("no, do X instead"), states a standing preference ("we always…", "never…"), or redirects an action the agent took under a skill or doc.
**Only persist a *durable* lesson** — one that generalizes and will recur. Skip one-off, task-specific tweaks that won't apply next time; persisting those pollutes the docs. Whenever unsure whether it generalizes, ask the user.
1. **Capture the lesson.** State, in one line, the general rule the feedback implies — not the surface incident ("Mock external HTTP in unit tests," not "the agent mocked the wrong call"). 2. **Locate the target.** Settle scope first: would the lesson hold in another project? No → a project doc, rule or wrapper, never a shared generic skill. Yes → the governing skill or doc, shared ones included, edited at its canonical source when the installed copy is a symlink or sync — the proposal says so. Find which skill/doc governs this action (search skills, `AGENTS.md`/`CLAUDE.md`, convention docs); when the repo defines a doc-placement guide (e.g. `.agents/docs/README.md`), follow it for locating and creating targets. If one exists, it's the target — and if that rule already existed yet failed to steer the agent, the discoverability gap *is* the lesson, not a no-op: don't stop at "the rule exists." Diagnose why it didn't fire (buried, in a doc the agent wouldn't open for this action, scoped or worded too narrowly, or unenforced) and fix that root cause: surface it where the agent looks, tighten its scope, cross-reference it, or enforce it mechanically. If none fits, propose a new target and ask before drafting: a check for a mechanical lesson (below), a new skill for a recurring workflow, a new rule for a standing constraint, or the most fitting doc otherwise; a new doc comes with its entry-file index line and read-when hook, or nothing ever loads it. Ask whenever unsure.
propose a deterministic check over prose; the check is declined, or no tooling can host it (the proposal says so) → write the rule. Read the repo's check scripts and CI first: wire or repair an existing check rather than add one.
a rule that matters only when reviewing goes in a review-time doc, not implementation context. 3. **Draft the edit.** Write the rule into the target as the least text that fully captures it: agent-agnostic ("the agent", never a vendor name), no process narration, no restating — a real durable instruction. Prefer tightening or extending an existing ru
A collection of generic agentic tools for common engineering tasks, designed to work with any AI agent on any kind of software project.
Make a project agent-ready by converging it toward a canonical agent-neutral structure. Re-runnable, and doubles as an audit.
Attach pasted images, files or URLs to a fetched ticket, saved beside its ticket file and referenced from it, or fill an…
Check how much of a ticket is already implemented and save a per-requirement status report.
Draft, rewrite, or refine a doc for maximum token economy without losing any rule or intent. Use for docs kept in version control…
Author or refine a skill for maximum token economy without losing intent. Use when creating any new skill or editing an existing…
Audit what auto-loads into an agent session's context window and suggest lean, reversible fixes to cut startup tokens.
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.