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 jcottam/agent-resources --skill review-prgit clone --depth 1 https://github.com/jcottam/agent-resourcesWrote 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/jcottam/agent-resources/review-pr)<a href="https://agentmods.dev/skills/jcottam/agent-resources/review-pr"><img src="https://agentmods.dev/badge/skills/jcottam/agent-resources/review-pr/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/jcottam/agent-resources/review-pr"><img src="https://agentmods.dev/badge/skills/jcottam/agent-resources/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 381 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00112 | $0.03617 |
| Opus 5.5 | $0.00045 | $0.01447 |
| Sonnet 5.5 | $0.00022 | $0.00723 |
| Haiku 4.5 | $0.00011 | $0.00362 |
Grade A, and why
review-pr 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 — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review PR
Forensic, stage-aware pull request review. Reconstructs the commit narrative, tests the PR's architectural premises against project reality, and produces a review comment the user can post directly.
Three core insights:
- Most bad reviews happen because the reviewer looks at the final diff in isolation and misses the why.
- Most over-engineered PRs happen because the contributor builds for imagined future requirements instead of the current problem.
- Most shallow reviews happen because the reviewer catalogs file-level findings without first understanding what the change means for the product. Think about the product impact before diving into the code.
Phase 1 — Orientation
Before reading any code, establish context.
1. Get PR metadata
git remote -v
GitHub (primary path):
gh pr view <N> --json baseRefName,headRefName,title,body,commits,files,statusCheckRollup,reviews
Fallback (no gh CLI or non-GitHub remote):
git log --oneline <base-branch>..<pr-branch>
git diff --stat <base-branch>...<pr-branch>
Use the resolved base/head branch names for all subsequent commands.
2. Read project conventions
Before forming opinions, read the project's own rules:
AGENTS.md— architecture, boundaries, "always do / never do" lists.cursor/rules/— workspace rules that apply to all changesCONTRIBUTING.md,.github/PULL_REQUEST_TEMPLATE.mdif present
If none of these exist, infer conventions from the existing codebase: look at 2–3 files in the same directory as the PR's primary changes. Match naming, error handling patterns, test structure, and abstraction level already established.
These are the standards the PR should be measured against, not generic best practices.
3. Read the PR description and commit messages
git log <base-branch>..<pr-branch> --reverse --format="%h %s%n%n%b"
Extract what the PR claims to do. Do not treat claims as fact until the diff confirms them. Form your own judgment of scope and risk before reading existing review comments or the user's opinion.
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 · 388 lines · 112 tokens per session scan A bc168905d284
review-pr is a skill published in the GitHub repository jcottam/agent-resources (29 stars, last pushed 2d ago), licensed MIT. It adds 112 tokens to every session and 3,617 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 2026-08-30.
Other skills, from other repositories
pr-review-comments
Posts review findings from a JSON file as inline comments on a GitHub Pull Request, attaching each comment to its file and line. Use when you have a list/JSON of review findings (each with a file path, line number, and a message such as summary/failurescenario) and want them published on a PR as inline review…
create-pull-request
Create and manage pull requests using GitHub CLI. Covers branch preparation, writing PR titles and descriptions, creating PRs, handling review feedback, and merge/cleanup workflows. Use when proposing changes from a feature or fix branch for review, merging completed work into the main branch, requesting code review…
audit-pr
Audit a whole PR against the delivery contract and return MERGE-READY or evidenced blockers with the full URL. Consumes the current review-change REVIEW-PASS receipt instead of re-running review axes; posts a SHA-bound ready comment; never edits or merges. Triggers: "audit-pr", "is this PR ready", "merge gate".
hashiiiii-pull-request
Use this skill to create or edit a GitHub pull request with the repository template or the default structure.
pull-request-feedback
Use when working through review feedback on a GitHub pull request — reading review and inline comments one by one, discussing and making changes, replying or reacting, then pushing and re-requesting review. Trigger on "review the PR feedback", "go through the comments", "address review feedback".
hashiiiii-explain-pr
Use when a user asks to understand or explain a pull request's purpose, diff, or relationship to an issue.