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 elisaterumi-ai/agent-skills-in-practice --skill pr-reviewgit clone --depth 1 https://github.com/elisaterumi-ai/agent-skills-in-practiceWrote 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/elisaterumi-ai/agent-skills-in-practice/pr-review)<a href="https://agentmods.dev/skills/elisaterumi-ai/agent-skills-in-practice/pr-review"><img src="https://agentmods.dev/badge/skills/elisaterumi-ai/agent-skills-in-practice/pr-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/skills/elisaterumi-ai/agent-skills-in-practice/pr-review"><img src="https://agentmods.dev/badge/skills/elisaterumi-ai/agent-skills-in-practice/pr-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 | $0.00028 | $0.00147 |
| Opus 5 | $0.00014 | $0.00073 |
| Sonnet 5 | $0.00006 | $0.00029 |
| Haiku 4.5 | $0.00003 | $0.00015 |
Grade A, and why
pr-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 12d 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.
What it actually says
Instructions
When reviewing a pull request:
- Analyze the code changes (diff)
- Identify potential bugs or edge cases
- Check readability and structure
- Evaluate performance implications
- Look for security issues (if applicable)
- Suggest improvements and alternatives
Output Format
Summary
Short explanation of what the PR does
Issues
- List of problems, risks, or concerns
Suggestions
- Improvements and recommendations
Positives
- What is well implemented
Risk Level
Low / Medium / 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.
- 12d ago First seen · 33 lines · 28 tokens per session scan A 8499a176a366
pr-review is a skill published in the GitHub repository elisaterumi-ai/agent-skills-in-practice (133 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 147 once invoked, about $0.0001 per session on Opus 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.
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Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…