Borrowing it
Nothing to install: this file belongs to phuryn/pm-brain. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/phuryn/pm-brain/main/.claude/skills/pm-brain/scaffold/.claude/commands/review.mdgit clone --depth 1 https://github.com/phuryn/pm-brainWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/phuryn/pm-brain/review)<a href="https://agentmods.dev/commands/phuryn/pm-brain/review"><img src="https://agentmods.dev/badge/commands/phuryn/pm-brain/review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/phuryn/pm-brain/review"><img src="https://agentmods.dev/badge/commands/phuryn/pm-brain/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.01185 |
| Opus 5.5 | $0.00000 | $0.00474 |
| Sonnet 5.5 | $0.00000 | $0.00237 |
| Haiku 4.5 | $0.00000 | $0.00119 |
Grade A, and why
review 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 1mo 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/review
The weekly maintenance sweep. Six checks. Produces a dated report and edits files directly where confidence is high.
Input
None, or an optional scope (/review hypotheses, /review stakeholders) to run a single check.
Loads
CLAUDE.md(operating principles, autonomy mode, memory promotion bar)docs/system-evolution.md(the 8 failure modes the sweep is designed to catch)- All durable areas in scope:
knowledge/,hypotheses/,decisions/,stakeholders/ - Recent
ingestion/for promotion candidates - The last 2
maintenance/log/entries to compare deltas
Updates
maintenance/log/<date>-review.md— the dated report- Direct edits to durable files where confidence is high: promote / demote hypotheses, update stakeholder
Last touched, archive shipped features past 90 days, compress duplicate insights - Drafts (not committed) for items that need PM judgment: stale strategy assumptions, unresolved tensions, decision debt
Surfaces
The six standard checks, with counts and the top item in each:
- Stale knowledge — files not updated in 6+ weeks
- Stale evidence — market past 30-60 days, interviews past 90, strategy assumptions past quarterly
- Hypothesis and decision hygiene — active hypotheses with no evidence in 30+ days, promoted hypotheses without decisions, triggered "what would reverse this" conditions, decision debt
- Stakeholder cadence and strategy tensions — high-influence stakeholders not touched in 3+ weeks, drift between recent decisions and strategy
- Knowledge synthesis (compression) — recurring patterns, recurring contradictions, candidates for
strategy.md § Tensions - Archival sweep — shipped features past 90 days, resolved hypotheses, old market intel
Compression is additive. Minority signals are preserved. Archive extracts durable lessons before removing.
Surfacing drift — cite, don't paraphrase
When /review flags drift on a promoted / validated hypothesis or a decided decision — i.e. fresh evidence has appeared that contradicts the original premise — the surfacing must name the specific contradicting signals, not paraphrase the conclusion.
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.
- 1mo ago First seen · 62 lines · 0 tokens per session scan A 41d5a9d68436
review is a command published in the GitHub repository phuryn/pm-brain (941 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,185 tokens. 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 2026-08-30.
Other commands, from other repositories
youtube
Extract transcript, metadata, and top comments from a YouTube video - summarized via Gemini (free tier) or Grok and saved to vault. Add --visual to also read the video's frames (scene detection).
obsidian-retrieval-eval
Measure how well vault search finds the right note for a natural-language question - recall@k and MRR, with the concrete failures.
x-read
Deep-read an X (Twitter) post via Grok xsearch - verbatim post, thread, TL;DR, claims, reply sentiment, voices to watch.
obsidian-checkin
Ask the owner whether old people and project notes still hold - shows what each note says and when it was last checked, re-asks until answered, saves the news.
obsidian-distill
Condense a long note or source into key claims, each tagged with provenance back to the exact source block it came from.
obsidian-merge
Merge two near-duplicate notes found by /obsidian-health into one - dry run by default, redirects the retired note rather than deleting it.