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.
git clone --depth 1 https://github.com/danielvm-git/bigpowersWrote 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/rules/danielvm-git/bigpowers/request-review)<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/request-review"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/request-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/rules/danielvm-git/bigpowers/request-review"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/request-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 | $0.00053 | $0.01292 |
| Opus 5.5 | $0.00021 | $0.00517 |
| Sonnet 5.5 | $0.00011 | $0.00258 |
| Haiku 4.5 | $0.00005 | $0.00129 |
Grade A, and why
request-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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
story: e45s28
Request Review
Dispatch fresh reviewer agents with clean contexts. Reviewers have no shared state — they find what the coding agent missed.
Distinct from audit-code: audit-code is self-review (internal). This skill dispatches external agents.
Solo developer note: Reviewer agents replace the human reviewer.
Run audit-code first. Don't waste reviewer attention on hygiene issues you could have caught yourself.
Santa Method — Dual-Blind AND Gate (e45s07)
Use two independent reviewers (Reviewer A and Reviewer B) with no shared context between them or the coding agent.
| Parameter | Value |
|---|---|
| Reviewers | 2 (mandatory) |
MAX_REVIEW_ITERATIONS |
5 (hard cap — e45s28; iteration 6 forbidden) |
| Pass rule | AND-gate — both reviewers must pass independently |
| Blindness | Neither reviewer sees the other's report until both complete |
Iteration loop (max MAX_REVIEW_ITERATIONS):
- Dispatch Reviewer A and Reviewer B in parallel with identical briefs but separate contexts.
- Collect both reports. Each categorizes findings: must-fix / should-fix / consider.
- AND-gate: If either reviewer has must-fix findings → FAIL round. Run
respond-review, fix, re-dispatch both reviewers. - If both pass (zero must-fix, score ≥ 94% each) → review complete.
- After 5 iterations without dual pass → stop; report "Review cap exhausted (5/5). Human decision required." Do not merge.
HARD GATE — Single-reviewer pass is insufficient. Partial agreement does not satisfy the AND-gate.
Process
1. Prepare the review brief
Write a self-contained brief for each reviewer. Include:
- What was built (feature description, not implementation)
- Which files changed (the diff context)
- What
specs/artifacts are relevant (activeepics/eNN-*.yaml,requirements/SCOPE_LATEST.yaml,bugs/BUG-*.md) - What CONVENTIONS.md requires
- What the verify command is
- What you're most uncertain about (where you want fresh eyes)
- Security focus — If the epic has a
specs/security/epics/<id>/THREAT_MODEL.md, include the relevant vulnerability categories as reviewer focal points. Also include the false-positive exclusion rules so the reviewer avoids known-safe patterns. Tag the review assecurity-sensitive: trueif THREAT_MODEL risk is HIGH+.
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 · 113 lines · 53 tokens per session scan A 785ae7750c49
request-review is a cursor rule published in the GitHub repository danielvm-git/bigpowers (267 stars, last pushed 27d ago), licensed MIT. It adds 53 tokens to every session and 1,292 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
Other cursor rules, from other repositories
clean-code
Apply language-agnostic clean-code discipline to all code writing, editing, reviewing, testing, and refactoring, including file placement, single responsibility, and verified completion.
boffin-post-change-audit
Pre-flight review and post-change kernel audit.
refactoring
Refactoring: systematic approach, extract/inline, guard clauses, early returns.
new-pull-request
Use this rule when requested to review a pull request.
ai-security-review
Rule Name: ai-security-review Description: Perform security review for any code that handles user input, authentication, database queries, or external API calls. Filters.
ai-code-review
Rule Name: ai-code-review Description: Always review code for security, performance, correctness, and maintainability before submitting. Filters.