agentic-actions-audito…
Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use…
Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory",
$ npx -y skills add waybarrios/opencode-power-pack --skill agents-md-revise --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/agents-md-reviseContext preview
The summary Claude sees to decide when to auto-load this skill.
Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory",
name: agents-md-revise description: Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory", "remember this for next time", or at the end of a productive session when valuable context has emerged that is not yet documented. This complements agents-md-improver — improver audits, while this one captures. license: Apache-2.0 (modified; see UPSTREAMS.json)
Review the current session for learnings about working in this codebase, then update the project-rules file with context that would help future sessions be more effective.
Read `../agents-md-improver/references/project-rule-resolution.md`, resolved relative to this loaded `SKILL.md` directory and not the consuming project's CWD or working directory, before target selection. Resolve the actual target client and phase instead of assuming that co-located files behave alike across OpenCode and Claude Code.
Look back over the session and identify what context was missing that would have helped the agent work more effectively. Examples:
Be selective. Only capture things that:
1. Will recur in future sessions (not one-off fixes). 2. Would have saved time if known up front. 3. Cannot be derived by reading the code.
Read the matrix before selecting a target. Use native file search or glob when available; otherwise recursively enumerate without silent result caps. Determine all of the following before proposing a write:
Decide where each addition belongs:
`.agents.local.md` and `.claude.local.md` are unsupported invented names. Warn about them and do not recommend them as targets.
If no effective file exists, propose the smallest supported layout for the identified clients and scope. Report any shadowed or omitted candidate with the client/version and startup or lazy phase that excludes it.
**Keep it concise.** The rules file is part of every prompt, so brevity matters. One line per concept when possible.
Format: `<command or pattern> — <brief description>`
**Avoid:**
**Prefer:**
Never put secret values in any prompt-loaded file, including local, global, imported, configured, managed, remote, or gitignored rules. A local or gitignored rule file is not a secret store. Replace any encountered value with `[REDACTED]` and identify only its location and type.
For each addition, show the user the diff before applying. Format:
### Update: ./AGENTS.md **Why:** [one-line reason this matters for future sessions] ```diff + [the a
54 rigorous skills for Codex, OpenCode, and Pi: code review, security audit, feature development, frontend design, MCP tools, Hugging Face ML/training, and more.
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