Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics.

MITAuto-check passedAgent Workflows

Install Review

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/auto-memory-pro/skills/review .claude/skills/review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review
GitHub stars
2.2k
Token cost
~1k tokens
SKILL.md length
340 words
Files
1
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics.

  • Works in 5 steps: Locate memory directory → Read and analyze MEMORY.md → Read topic files → …
  • Agent Workflows work in your project
  • SKILL.md covers Usage, What It Does, When to Use and Tips
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Review is an agent skill from LeoYeAI/openclaw-master-skills. Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Agent Workflows work in your project

Example prompts

  • “/review”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Locate memory directory
  2. Read and analyze MEMORY.md
  3. Read topic files
  4. Cross-reference with CLAUDE.md
  5. Generate report

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review loads about 1k tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 340 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 340 words, ~1,020 tokens.

Download SKILL.mdSave it as .claude/skills/review/SKILL.md (or your agent's skills folder).
name
review
description
Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics.
command
/si:review

/si:review — Analyze Auto-Memory

Performs a comprehensive audit of Claude Code's auto-memory and produces actionable recommendations.

Usage

/si:review                    # Full review
/si:review --quick            # Summary only (counts + top 3 candidates)
/si:review --stale            # Focus on stale/outdated entries
/si:review --candidates       # Show only promotion candidates

What It Does

Step 1: Locate memory directory
bash
# Find the project's auto-memory directory
MEMORY_DIR="$HOME/.claude/projects/$(pwd | sed 's|/|%2F|g; s|%2F|/|; s|^/||')/memory"

# Fallback: check common path patterns
# ~/.claude/projects/<user>/<project>/memory/
# ~/.claude/projects/<absolute-path>/memory/

# List all memory files
ls -la "$MEMORY_DIR"/

If memory directory doesn't exist, report that auto-memory may be disabled. Suggest checking with /memory.

Step 2: Read and analyze MEMORY.md

Read the full MEMORY.md file. Count lines and check against the 200-line startup limit.

Analyze each entry for:

  1. Recurrence indicators

    • Same concept appears multiple times (different wording)
    • References to "again" or "still" or "keeps happening"
    • Similar entries across topic files
  2. Staleness indicators

    • References files that no longer exist (find to verify)
    • Mentions outdated tools, versions, or commands
    • Contradicts current CLAUDE.md rules
  3. Consolidation opportunities

    • Multiple entries about the same topic (e.g., three lines about testing)
    • Entries that could merge into one concise rule
  4. Promotion candidates — entries that meet ALL criteria:

    • Appeared in 2+ sessions (check wording patterns)
    • Not project-specific trivia (broadly useful)
    • Actionable (can be written as a concrete rule)
    • Not already in CLAUDE.md or .claude/rules/
Step 3: Read topic files

If MEMORY.md references or the directory contains additional files (debugging.md, patterns.md, etc.):

  • Read each one
  • Cross-reference with MEMORY.md for duplicates
  • Check for entries that belong in the main file (high value) vs. topic files (details)
Step 4: Cross-reference with CLAUDE.md

Read the project's CLAUDE.md (if it exists) and compare:

  • Are there MEMORY.md entries that duplicate CLAUDE.md rules? (→ remove from memory)
  • Are there MEMORY.md entries that contradict CLAUDE.md? (→ flag conflict)
  • Are there MEMORY.md patterns not yet in CLAUDE.md that should be? (→ promotion candidate)

Also check .claude/rules/ directory for existing scoped rules.

Step 5: Generate report

Output format:

📊 Auto-Memory Review

Memory Health:
  MEMORY.md:        {{lines}}/200 lines ({{percent}}%)
  Topic files:      {{count}} ({{names}})
  CLAUDE.md:        {{lines}} lines
  Rules:            {{count}} files in .claude/rules/

🎯 Promotion Candidates ({{count}}):
  1. "{{pattern}}" — seen {{n}}x, applies broadly
     → Suggest: {{target}} (CLAUDE.md / .claude/rules/{{name}}.md)
  2. ...

🗑️ Stale Entries ({{count}}):
  1. Line {{n}}: "{{entry}}" — {{reason}}
  2. ...

🔄 Consolidation ({{count}} groups):
  1. Lines {{a}}, {{b}}, {{c}} all about {{topic}} → merge into 1 entry
  2. ...

⚠️ Conflicts ({{count}}):
  1. MEMORY.md line {{n}} contradicts CLAUDE.md: {{detail}}

💡 Recommendations:
  - {{actionable suggestion}}
  - {{actionable suggestion}}

When to Use

  • After completing a major feature or debugging session
  • When /si:status shows MEMORY.md is over 150 lines
  • Weekly during active development
  • Before starting a new project phase
  • After onboarding a new team member (review what Claude learned)

Tips

  • Run /si:review --quick frequently (low overhead)
  • Full review is most valuable when MEMORY.md is getting crowded
  • Act on promotion candidates promptly — they're proven patterns
  • Don't hesitate to delete stale entries — auto-memory will re-learn if needed

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/auto-memory-pro/skills/review of LeoYeAI/openclaw-master-skills.

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review compared with similar skills
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Review this skillLeoYeAI/openclaw-master-skills2.2k—~1kAutomated safety check: PassMIT
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Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k10 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79689 repos~8.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Review

What does Review do?

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Review is an agent skill from LeoYeAI/openclaw-master-skills. Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics.

When should I use Review?

Review fits situations like: agent Workflows work in your project.

How do I install Review in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill review -a claude-code`. Or copy the skill folder (skills/auto-memory-pro/skills/review in LeoYeAI/openclaw-master-skills) into .claude/skills/review in your project. Claude Code loads it when a task matches its description.

How do I install Review in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill review -a codex`. Or copy the skill folder (skills/auto-memory-pro/skills/review in LeoYeAI/openclaw-master-skills) into .agents/skills/review in your project. Codex loads it when a task matches its description.

Can I use Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review, .gemini/skills/review, .github/skills/review and .opencode/skills/review in your project.

What does Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Review is instructions for the agent only.

Does Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review use?

Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Review?

Skills that share tags, products or a category with Review: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.