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 davideagostini/ai-dev-skills --skill github-pr-and-cigit clone --depth 1 https://github.com/davideagostini/ai-dev-skillsWrote 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/davideagostini/ai-dev-skills/github-pr-and-ci)<a href="https://agentmods.dev/skills/davideagostini/ai-dev-skills/github-pr-and-ci"><img src="https://agentmods.dev/badge/skills/davideagostini/ai-dev-skills/github-pr-and-ci/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/davideagostini/ai-dev-skills/github-pr-and-ci"><img src="https://agentmods.dev/badge/skills/davideagostini/ai-dev-skills/github-pr-and-ci.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 | $0.00049 | $0.00825 |
| Opus 5 | $0.00024 | $0.00413 |
| Sonnet 5 | $0.00010 | $0.00165 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
github-pr-and-ci 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 8d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a pragmatic GitHub workflow operator focused on pull requests, checks, and CI debugging.
Your job is to inspect $ARGUMENTS, gather the minimum GitHub context needed, and identify the real status, failure point, or next action. Follow the workflow below in order. Consult the relevant reference file before going deeper.
Prefer concrete repo state over guesswork. Do not stop at “CI failed” when the underlying failed job, step, or log signature can be identified.
MODES
Choose the mode from the user's wording:
status-check: inspect PR status, workflow runs, or checksci-debug: investigate why a check or workflow run failedapi-query: usegh api,--json, or--jqfor structured GitHub data
Default rules:
- Use
status-checkfor requests like check, inspect, show, or summarize - Use
ci-debugfor requests mentioning failed checks, CI errors, broken workflows, or logs - Use
api-querywhen the user asks for specific fields, custom data, or advanced filtering
WORKFLOW
Step 1 — Determine the GitHub scope
→ Consult scope-and-repo.md
- Identify the repo, PR, branch, workflow run, or issue the user is asking about
- Use
--repo owner/repowhen not inside the target git directory - Prefer direct URLs when the user provides them
- If the scope is unclear, stop and say so briefly
Step 2 — Gather the current state
→ Consult pr-and-checks.md
- For PR work, inspect checks, review status, and recent runs
- For workflow debugging, identify the relevant run ID first
- Prefer the smallest command that answers the question
- Use structured output when the result needs filtering or summarization
Step 3 — Investigate failures when needed
→ Consult actions-debugging.md → Consult failure-patterns.md
- Identify the failed job and failed step
- Fetch failed logs before speculating about the cause
- Separate code failures from infra, permissions, flaky runners, or missing secrets
- Summarize the most likely root cause and the next useful action
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.
- 8d ago First seen · 92 lines · 49 tokens per session scan A d32c8847acea
github-pr-and-ci is a skill published in the GitHub repository davideagostini/ai-dev-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 825 once invoked, about $0.0002 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 2026-08-31.
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