Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
[REDACTED] and retain only the minimum location, type, and remediation evidence.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:
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:
@ imports relative to each containing file. Track canonical visited paths for cycle detection, stop at the verified maximum of four import hops, and, before reading an import outside the project, obtain explicit user approval.Decide where each addition belongs:
AGENTS.md plus a Claude CLAUDE.md containing @AGENTS.md when both clients are required. Claude-only additions may follow the import.CLAUDE.local.md is Claude-native, but not OpenCode-native..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:
pnpm i --frozen-lockfile after pulling")dev script binds to port 3000 — kill any other process on that port first")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 addition — keep it brief]
```
If multiple additions go to the same file, group them under one header so the user can review the whole change in one view.
Ask the user explicitly: "Apply these changes?" Edit only files they approve.
Preserve the existing structure. Place additions in the most relevant section (e.g., a new build command goes under "Commands" if that section exists). If no obvious section fits, create one with a clear header.
If the user rejects an addition, do not retry it in the same session — they may have a reason. Move on.
agents-md-improver for the full maintenance loop: improver audits and identifies gaps; this one captures fresh session-specific learnings.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or when the codebase has changed enough that the rules file may be stale. Scans the repository for every rules file, grades each against a quality rubric, outputs a quality report, and applies targeted edits only after user approval.
日本語の概要は準備中です。原文の説明を表示しています。
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.
日本語の概要は準備中です。原文の説明を表示しています。
Design a feature architecture by analyzing existing codebase patterns and conventions, then provide a comprehensive implementation blueprint with specific files to create or modify, component designs, data flows, and a build sequence. Use this skill when the user asks for an architecture design, an implementation plan for a non-trivial feature, or when dispatched as a sub-task during feature-dev architecture phase.
日本語の概要は準備中です。原文の説明を表示しています。
Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
日本語の概要は準備中です。原文の説明を表示しています。
Agents should invoke this skill for code reviews, linting/formatting setup, maintainability checks, complexity concerns, warning cleanup, coding standards, or quality gates in Rust, TypeScript, Python, shell, and mixed repos.
日本語の概要は準備中です。原文の説明を表示しています。