Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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。
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity
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。
Attribution: Sourced from alirezarezvani/claude-skills by Alireza Rezvani.
Auto-memory captures. This plugin curates.
Claude Code's auto-memory (v2.1.32+) automatically records project patterns, debugging insights, and your preferences in MEMORY.md. This plugin adds the intelligence layer: it analyzes what Claude has learned, promotes proven patterns into project rules, and extracts recurring solutions into reusable skills.
| Command | What it does |
|---|---|
/si:review | Analyze MEMORY.md — find promotion candidates, stale entries, consolidation opportunities |
/si:promote | Graduate a pattern from MEMORY.md → CLAUDE.md or .claude/rules/ |
/si:extract | Turn a proven pattern into a standalone skill |
/si:status | Memory health dashboard — line counts, topic files, recommendations |
/si:remember | Explicitly save important knowledge to auto-memory |
┌─────────────────────────────────────────────────────────┐
│ Claude Code Memory Stack │
├─────────────┬──────────────────┬────────────────────────┤
│ CLAUDE.md │ Auto Memory │ Session Memory │
│ (you write)│ (Claude writes)│ (Claude writes) │
│ Rules & │ MEMORY.md │ Conversation logs │
│ standards │ + topic files │ + continuity │
│ Full load │ First 200 lines│ Contextual load │
├─────────────┴──────────────────┴────────────────────────┤
│ ↑ /si:promote ↑ /si:review │
│ Self-Improving Agent (this plugin) │
│ ↓ /si:extract ↓ /si:remember │
├─────────────────────────────────────────────────────────┤
│ .claude/rules/ │ New Skills │ Error Logs │
│ (scoped rules) │ (extracted) │ (auto-captured)│
└─────────────────────────────────────────────────────────┘
/plugin marketplace add alirezarezvani/claude-skills
/plugin install self-improving-agent@claude-code-skills
clawhub install self-improving-agent
./scripts/codex-install.sh --skill self-improving-agent
| File | Who writes | Scope | Loaded |
|---|---|---|---|
./CLAUDE.md | You (+ /si:promote) | Project rules | Full file, every session |
~/.claude/CLAUDE.md | You | Global preferences | Full file, every session |
~/.claude/projects/<path>/memory/MEMORY.md | Claude (auto) | Project learnings | First 200 lines |
~/.claude/projects/<path>/memory/*.md | Claude (overflow) | Topic-specific notes | On demand |
.claude/rules/*.md | You (+ /si:promote) | Scoped rules | When matching files open |
1. Claude discovers pattern → auto-memory (MEMORY.md)
2. Pattern recurs 2-3x → /si:review flags it as promotion candidate
3. You approve → /si:promote graduates it to CLAUDE.md or rules/
4. Pattern becomes an enforced rule, not just a note
5. MEMORY.md entry removed → frees space for new learnings
Auto-memory is excellent at recording what Claude learns. But it has no judgment about:
That's what this plugin does.
When you promote a learning, it moves from Claude's scratchpad (MEMORY.md) to your project's rule system (CLAUDE.md or .claude/rules/). The difference matters:
Promoted rules have higher priority and load in full (not truncated at 200 lines).
Not everything belongs in CLAUDE.md. Use .claude/rules/ for patterns that only apply to specific file types:
# .claude/rules/api-testing.md
---
paths:
- "src/api/**/*.test.ts"
- "tests/api/**/*"
---
- Use supertest for API endpoint testing
- Mock external services with msw
- Always test error responses, not just happy paths
This loads only when Claude works with API test files — zero overhead otherwise.
Analyzes MEMORY.md and topic files to identify:
Takes a proven pattern and generates a complete skill:
/plugin install or clawhub publishMonitors command output for errors. When detected, appends a structured entry to auto-memory with:
Token overhead: Zero on success. ~30 tokens only when an error is detected.
| Platform | Memory System | Plugin Works? |
|---|---|---|
| Claude Code | Auto-memory (MEMORY.md) | ✅ Full support |
| OpenClaw | workspace/MEMORY.md | ✅ Adapted (reads workspace memory) |
| Codex CLI | AGENTS.md | ✅ Adapted (reads AGENTS.md patterns) |
| GitHub Copilot | .github/copilot-instructions.md | ⚠️ Manual promotion only |
playwright-pro — sister plugin in the upstream repo (not bundled here; see the testing/ category for Playwright skills)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
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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。
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
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。
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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。