Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/stuartshields/claude-setup/review-memorynpx skills add stuartshields/claude-setup --skill review-memorygit clone --depth 1 https://github.com/stuartshields/claude-setupWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00035 | $0.01383 |
| Opus 5 | $0.00017 | $0.00691 |
| Sonnet 5 | $0.00007 | $0.00277 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
review-memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: review-memory
When to Use
Run /review-memory when prompted by the memory review hook, or any time you want to audit what auto-memory has captured for this project. Use after completing a milestone, before starting new work, or when memory feels noisy.
Do NOT run this mid-task. Finish what you're working on first.
Mode Selection
- Full mode (default): Reads all topic files, presents detailed categorisation table, acts on confirmation.
- Compact mode (
/review-memory --compact): Quick list of new memories with one-line summaries. Asks "promote, keep, or remove?" for each. No topic file reads. Use when context is low or time is short.
Full Mode
Step 1: Load Memory
Read MEMORY.md from the project's memory directory. The path follows this pattern:
~/.claude/projects/<project-path-encoded>/memory/MEMORY.md
Where <project-path-encoded> is the project root path with / replaced by -.
Also read any topic files referenced from MEMORY.md (e.g., feedback_testing.md, project_auth.md).
List what was found:
- Total entries in MEMORY.md
- Topic files and their one-line descriptions
- Last modified dates
Step 2: Categorise Each Entry
For each memory entry, evaluate all three categories in this order:
- Remove? Is this stale, wrong, duplicated by CLAUDE.md/rules, or derivable from code/git? If yes → Remove.
- Promote? Does this encode a convention, decision, or constraint that should survive memory cleanup? If losing it would cause mistakes in future sessions, it belongs in CLAUDE.md, a rule file, or a skill → Promote.
- Keep only if the entry is still relevant but too situational or temporary for a permanent file (e.g., user preferences, in-flight research, external context not derivable from code).
Every "Keep" must include a one-line justification for why it doesn't belong in CLAUDE.md, a rule, or a skill. If you can't articulate why, it's probably a Promote.
Present the categorisation as a table:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 141 lines · 35 tokens per session scan A 795847b80419
review-memory is a skill published in the GitHub repository stuartshields/claude-setup (2 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 1,383 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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