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 getpapi/papi --skill pr-reviewergit clone --depth 1 https://github.com/getpapi/papiWrote 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/getpapi/papi/pr-reviewer)<a href="https://agentmods.dev/skills/getpapi/papi/pr-reviewer"><img src="https://agentmods.dev/badge/skills/getpapi/papi/pr-reviewer/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/getpapi/papi/pr-reviewer"><img src="https://agentmods.dev/badge/skills/getpapi/papi/pr-reviewer.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 | $0.00040 | $0.00813 |
| Opus 5.5 | $0.00016 | $0.00325 |
| Sonnet 5.5 | $0.00008 | $0.00163 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
pr-reviewer 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 today.
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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review a pull request or build
Resolve the actual skill directory from this SKILL.md before using references or scripts. Use the host's available tools; slash commands, Bash, Task and Skill are not universal APIs.
Gather the current review scope
Read the requested PR metadata, exact head commit, diff, existing reviews, owning rules and handoff. For a branch-only review, fetch the base and read the scoped diff. Preserve dirty work; reuse an isolated existing checkout when appropriate. Do not infer a task from one branch naming pattern: shared cycle branches can contain multiple tasks.
Prefer existing GitHub tools or gh pr view, gh pr diff and gh pr checks. The optional helper <absolute-skill-dir>/scripts/fetch_pr_data.py <PR_URL> --no-clone --output-dir <owned-staging> collects the same evidence. It is not required; do not install dependencies, clone again or generate client command files just to review.
Use the owning project's staging directory. On Windows use an owned subdirectory of C:/Develop/Claude/build-temp; on Linux use native storage. Never delete another review's files or overwrite a live checkout.
Review the owning source
Use review criteria as a reference, scaled to the actual change:
- Does the implementation satisfy the handoff and intended behavior? Trace callers, failure paths, boundaries and affected documentation.
- Check security, authentication, tenancy, secrets and data-access predicates before pagination.
- Check null/empty inputs, type narrowing, exceptions, races, cancellation and stale results.
- Evaluate simplicity, ownership and reuse. Fix the shared owner rather than duplicating behavior.
- Examine meaningful owning tests and actual production-entrypoint evidence. Follow the repository's check policy and resource ceiling; do not duplicate a valid qualification receipt.
Distinguish introduced defects, required corrections, pre-existing issues and optional suggestions. Each actionable finding names a verified path/line, impact, severity and concrete correction. Do not manufacture findings or praise to fill a template. Static inspection is not runtime proof.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 45 lines · 40 tokens per session scan A 6e71718fbfa4
pr-reviewer is a skill published in the GitHub repository getpapi/papi (11 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 813 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 2026-10-16.
Other skills, from other repositories
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…
branch-pr
Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
chained-pr
Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.
revert
Git-aware revert that understands Draft tracks, phases, and tasks. Safely undo work at task, phase, or track level. Use when the user asks to 'revert this track', 'undo a phase', 'revert task X', or says 'roll back the last task', 'undo this work'.