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 skills add axiomantic/spellbook --skill reviewing-prsgit clone --depth 1 https://github.com/axiomantic/spellbookWrote 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/skills/axiomantic/spellbook/reviewing-prs)<a href="https://agentmods.dev/skills/axiomantic/spellbook/reviewing-prs"><img src="https://agentmods.dev/badge/skills/axiomantic/spellbook/reviewing-prs/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/skills/axiomantic/spellbook/reviewing-prs"><img src="https://agentmods.dev/badge/skills/axiomantic/spellbook/reviewing-prs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00105 | $0.01475 |
| Opus 5.5 | $0.00042 | $0.00590 |
| Sonnet 5.5 | $0.00021 | $0.00295 |
| Haiku 4.5 | $0.00011 | $0.00147 |
Grade A, and why
reviewing-prs 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewing PRs Safely
Invariant Principles
- Determine review_source First: Never dispatch a PR review subagent without computing
review_source. No exceptions. - DIFF_ONLY Means No Local File Reads: In
DIFF_ONLYmode, local files for changed paths are on the wrong branch. Reading them produces wrong verdicts. - REFUTED Requires Branch-Accurate Source: A
REFUTEDverdict based on a local file read inDIFF_ONLYmode is a wrong verdict. Mark itINCONCLUSIVEor[NEEDS VERIFICATION]. - Inject Review Context Into Every Subagent: The mandatory injection block (mode, SHA, working directory, changed files) is non-optional.
The Wrong-Branch Failure
When reviewing a PR via diff, local files are on a different branch. Reading them produces silently wrong results:
- PR-introduced changes appear absent (local has old code)
- Real bugs get declared "not present" → false REFUTED verdicts
- Findings carry high confidence in factually wrong conclusions
This is a structural failure: the agent reads the wrong version of the file.
Review Source Decision
Before dispatching any code review subagent, determine review_source:
PR_HEAD_SHA=$(gh pr view <PR_NUMBER> --json headRefOid --jq '.headRefOid')
LOCAL_HEAD=$(git rev-parse HEAD)
PR_BRANCH=$(gh pr view <PR_NUMBER> --json headRefName --jq '.headRefName')
WORKTREE_PATH=$(git worktree list --porcelain | grep -B1 "branch refs/heads/$PR_BRANCH" | grep "^worktree" | awk '{print $2}')
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 · 132 lines · 105 tokens per session scan A 1b636bd4c831
reviewing-prs is a skill published in the GitHub repository axiomantic/spellbook (11 stars, last pushed today), licensed MIT. It adds 105 tokens to every session and 1,475 once invoked, about $0.0004 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 skills, from other repositories
autofix-pr
Watch a pull request and fix it from a worktree of its own - CI failures, review feedback from trusted authors and merge conflicts are fixed, pushed to the PR branch and answered on the PR under the user's git and gh identity. Usage - /autofix-pr [ | ] [--once] [--every ] [--no-reply] [--yes] [instructions]…
triage
Gatekeep and review GitHub issues and pull requests for Qwen Code maintainers. Use for GitHub Action issue triage, PR admission checks, product-direction review, KISS-focused PR review, and staged bilingual GitHub comments.
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit…
review-pr
Perform a comprehensive code review of a pull request.
pr
Analyze changes, detect scope issues, and create a well-structured PR.
validate-changes
Evaluate staged changes using LLM-as-a-Judge before committing.