Agent skill

Memory Review

by alirezarezvani in alirezarezvani/claude-skills

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

MITAuto-check passedAgent Workflows

Install Memory Review

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill memory-review -a claude-code

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

GitHub CLI
$ gh skill install alirezarezvani/claude-skills memory-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/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering-team/self-improving-agent/skills/memory-review .claude/skills/memory-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
memory-review
GitHub stars
28k
Token cost
~1.1k tokens
SKILL.md length
340 words
Files
1
Skills in repo
342
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 → …
  • The user runs /si:memory-review
  • 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

Memory Review is an agent skill from alirezarezvani/claude-skills. Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:memory-review or asks what has been learned and what should be promoted or pruned.

Its SKILL.md is about 1.1k 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: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The user runs /si:memory-review
  • Asks what has been learned and what should be promoted

Example prompts

  • “/memory-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 19392f7. 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

Memory Review loads about 1.1k tokens when it runs. Until then it costs about 58 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
~58
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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 alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 340 words, ~1,057 tokens.

Download SKILL.mdSave it as .claude/skills/memory-review/SKILL.md (or your agent's skills folder).
name
memory-review
description
Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:memory-review or asks what has been learned and what should be promoted or pruned.

/si:memory-review — Analyze Auto-Memory

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

Usage

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

© alirezarezvani, 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 engineering-team/self-improving-agent/skills/memory-review of alirezarezvani/claude-skills.

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Memory 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.

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Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

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Categories

Questions about Memory Review

What does Memory Review do?

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

When should I use Memory Review?

Memory Review fits situations like: the user runs /si:memory-review; asks what has been learned and what should be promoted.

How do I install Memory Review in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill memory-review -a claude-code`. Or copy the skill folder (engineering-team/self-improving-agent/skills/memory-review in alirezarezvani/claude-skills) into .claude/skills/memory-review in your project. Claude Code loads it when a task matches its description.

How do I install Memory Review in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill memory-review -a codex`. Or copy the skill folder (engineering-team/self-improving-agent/skills/memory-review in alirezarezvani/claude-skills) into .agents/skills/memory-review in your project. Codex loads it when a task matches its description.

Can I use Memory 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 alirezarezvani/claude-skills --skill memory-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/memory-review, .gemini/skills/memory-review, .github/skills/memory-review and .opencode/skills/memory-review in your project.

What does Memory Review need to run?

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

Does Memory 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 Memory 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 Memory Review use?

Memory 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 Memory Review use?

About 1.1k tokens (SKILL.md is roughly 4.2k 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 Memory Review?

Skills that share tags, products or a category with Memory 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, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Memory Review?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,829 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

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