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 KunanonJ/ai-skills-hub --skill github-pr-reviewgit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/github-pr-review)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/github-pr-review"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/github-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/kunanonj/ai-skills-hub/github-pr-review"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/github-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 | $0.00095 | $0.02836 |
| Opus 5 | $0.00048 | $0.01418 |
| Sonnet 5 | $0.00019 | $0.00567 |
| Haiku 4.5 | $0.00010 | $0.00284 |
Grade A, and why
github-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 9d 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.
This is a copy
100% identical to github-pr-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub PR review
Resolves Pull Request review comments with severity-based prioritization, fix application, and thread replies.
Current PR
!gh pr view --json number,title,state,milestone -q '"PR #\(.number): \(.title) (\(.state)) | Milestone: \(.milestone.title // "none")"' 2>/dev/null
Core workflow
1. Fetch, filter, and classify comments
REPO=$(gh repo view --json nameWithOwner -q '.nameWithOwner')
PR=$(gh pr view --json number -q '.number')
LAST_PUSH=$(git log -1 --format=%cI HEAD)
# Inline review comments - filter out replies (keep only originals)
gh api repos/$REPO/pulls/$PR/comments?per_page=100 --jq '
[.[] | select(.in_reply_to_id == null) |
{id, path, user: .user.login, created_at, body: .body[0:200]}]
'
# PR-level reviews with non-empty body (CodeRabbit sections, Gemini, etc.)
gh api repos/$REPO/pulls/$PR/reviews?per_page=100 --jq '
[.[] | select(.body | length > 0) |
{id, user: .user.login, state, submitted_at, body: .body[0:500]}]
'
Cross-check review-attached comments: CodeRabbit's review body states "Actionable comments posted: N". If the general pulls/$PR/comments endpoint returns fewer than N new originals from that reviewer, some comments are only available via the review-specific endpoint. Fetch them and merge by comment ID:
# $REVIEW_ID from the reviews fetch above; $EXPECTED from parsing "Actionable comments posted: N"
gh api repos/$REPO/pulls/$PR/reviews/$REVIEW_ID/comments?per_page=100 --jq '
[.[] | select(.in_reply_to_id == null) |
{id, path, user: .user.login, created_at, body: .body[0:200]}]
'
Deduplicate by id before continuing. Comments found only via the review-specific endpoint are valid inline comments and should be treated identically (same classification, same in_reply_to reply mechanism).
Filter new vs already-seen: compare created_at/submitted_at with $LAST_PUSH. Comments posted after the last push are new. Mark older comments as "previous round" in the summary table.
What ships with it
2 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.
- 9d ago First seen · 217 lines · 95 tokens per session scan A 77cc65f1c2aa
github-pr-review is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,836 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to github-pr-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
github-commenting
How to post clean, rich, deduplicated GitHub PR review comments — suggestion blocks, multi-line anchors, markers, formatting rules. Load before posting or fixing any PR comment.
armada-pr
PR-first finish for a feature lane. Use before reporting a feature done. Triggers on: PR, finish feature, gh pr create, merge, lane complete.
code-review-loop
Use when opening a PR for review or when receiving review feedback. Activate for keywords like "code review", "PR review", "request review", "review feedback", "address comments", "reviewer said". Covers both ends of the loop: preparing a reviewable PR and acting on feedback rigorously. Always engage with every…
ship
Create a rich PR from planning artifacts (SUMMARY one-liners, requirement coverage, verification status).
ticketcreate-pr
Create pull request with aggressive security and architecture review.
ticketreview-commit
Thorough code review, verify requirements met, commit with detailed message.