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 wangke19/gemini-ai-helpers --skill coderabbit-rules-from-pr-reviewsgit clone --depth 1 https://github.com/wangke19/gemini-ai-helpersWrote 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/wangke19/gemini-ai-helpers/coderabbit-rules-from-pr-reviews)<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/coderabbit-rules-from-pr-reviews"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/coderabbit-rules-from-pr-reviews/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/wangke19/gemini-ai-helpers/coderabbit-rules-from-pr-reviews"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/coderabbit-rules-from-pr-reviews.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 | $0.00026 | $0.01145 |
| Opus 5 | $0.00013 | $0.00573 |
| Sonnet 5 | $0.00005 | $0.00229 |
| Haiku 4.5 | $0.00003 | $0.00114 |
Grade A, and why
CodeRabbit Rules from PR Reviews - Fetch Comments 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 7d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeRabbit Rules from PR Reviews - Fetch Comments
This skill runs a Python script that fetches human review comments from recent merged PRs in a given GitHub repository. It handles all GitHub API calls, bot filtering, noise removal, rate limiting, and pagination, returning clean JSON output for AI analysis.
When to Use This Skill
Use this skill as Step 2-3 of the /teams:coderabbit-rules-from-pr-reviews command to collect review comments. The script replaces manual gh api calls with a single Python invocation.
Prerequisites
- GitHub CLI (
gh): Must be installed and authenticated. - Python 3: Python 3.6 or later.
Script Location
extensions/teams/skills/coderabbit-rules-from-pr-reviews/fetch_pr_comments.py
Usage
# Default: 30 most recent merged PRs
python3 extensions/teams/skills/coderabbit-rules-from-pr-reviews/fetch_pr_comments.py openshift/origin
# Custom count
python3 extensions/teams/skills/coderabbit-rules-from-pr-reviews/fetch_pr_comments.py openshift/origin --count 50
# Full URL
python3 extensions/teams/skills/coderabbit-rules-from-pr-reviews/fetch_pr_comments.py https://github.com/openshift/origin
What the Script Does
- Parses the repo argument — accepts
owner/repoor full GitHub URL - Fetches recent merged PRs via
gh pr list - For each PR, fetches two types of comments:
- Inline code review comments (
/pulls/{number}/comments) - General discussion comments (
/issues/{number}/comments)
- Inline code review comments (
- Filters out noise:
- Bot accounts: logins ending in
[bot]or matching known bots (coderabbitai,openshift-ci,openshift-bot,openshift-merge-robot,codecov,dependabot,renovate,k8s-ci-robot, etc.) - Prow commands: comments where every line starts with
/ - Approvals:
/lgtm,/approve,/hold, etc. - Short comments: less than 20 characters
- Bot accounts: logins ending in
- Rate limiting: 0.5s sleep between API calls, with retry logic for rate limit errors
Output Format
What ships with it
1 file 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.
- 7d ago First seen · 122 lines · 26 tokens per session scan A 6cfb7781542c
CodeRabbit Rules from PR Reviews - Fetch Comments is a skill published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 1,145 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 2026-09-03.
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