GitHub Agentic Workflows is a GitHub CLI extension that lets developers define AI-assisted repository automation in Markdown and run it through GitHub Actions. It is intended for tasks requiring interpretation or reasoning, such as issue triage, pull-request review, CI investigation, documentation maintenance, and dependency analysis. The catalogue entries provide skills and agents for working with these workflows.
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 github/gh-aw --skill github-scriptgit clone --depth 1 https://github.com/github/gh-awWrote 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/github/gh-aw/github-script)<a href="https://agentmods.dev/skills/github/gh-aw/github-script"><img src="https://agentmods.dev/badge/skills/github/gh-aw/github-script/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/github/gh-aw/github-script"><img src="https://agentmods.dev/badge/skills/github/gh-aw/github-script.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00015 | $0.00422 |
| Opus 5.5 | $0.00006 | $0.00169 |
| Sonnet 5.5 | $0.00003 | $0.00084 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
github-script 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 1mo 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
GitHub Action Script Best Practices
Use these guidelines for JavaScript executed by actions/github-script@v8.
Important Notes
- This action provides
@actions/coreand@actions/githubpackages globally - Do not add import or require for
@actions/core - Reference documentation:
Best Practices
- Use
core.info,core.warning,core.errorfor logging, notconsole.logorconsole.error - Use
core.setOutputto set action outputs - Use
core.exportVariableto set environment variables for subsequent steps - Use
core.getInputto get action inputs, withrequired: truefor mandatory inputs - Use
core.setFailedto mark the action as failed with an error message
Step Summary
Use core.summary.* function to write output the step summary file.
- Use
core.summary.addRaw()to add raw Markdown content (GitHub Flavored Markdown supported) - Make sure to call
core.summary.write()to flush pending writes - Summary function calls can be chained, e.g.
core.summary.addRaw(...).addRaw(...).write()
Common Errors
- Avoid
anytype as much as possible, use specific types orunknowninstead - Catch handler: check if error is an instance of Error before accessing message property
catch (error) {
core.setFailed(error instanceof Error ? error : String(error));
}
core.setFailedalso callscore.error, so do not call both
Typechecking
Run make js to run the typescript compiler.
Run make lint-cjs to lint the files.
Run make fmt-cjs after editing to format the file.
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.
- 1mo ago First seen · 54 lines · 15 tokens per session scan A 4976d84ad71f
github-script is a skill published in the GitHub repository github/gh-aw (5,406 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 422 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
watch-commit
Watch a GitHub commit for CI status changes using the gh-watch extension. Use when the user wants to monitor a commit's CI checks, wait for a build to finish, or track CI progress on a specific SHA.
ci-cd
CI/CD pipelines for GitHub Actions and Docker-based deployments — lint, test, build, push, deploy stages; environment secrets; branch-gated workflows; health-check rollbacks; and PM2/systemd service restarts.
Code Coverage Analysis
Measure and enforce test coverage with Istanbul/nyc, c8, Jest, and Vitest. Covers branch versus line coverage, per-directory thresholds, CI gates, and correctly excluding generated code from reports.
Checkly Monitoring as Code
Teach agents to build synthetic monitoring as code with Checkly, including Playwright browser checks, API checks, alerting, and CI deploy workflows.
CI Test Sharding Parallelization
Teach agents to shard and parallelize Playwright, Jest, and pytest suites in CI to reduce wall-clock time while merging reports reliably.
GitHub CI Fix Debugging
Debug and fix failing GitHub PR checks by inspecting GitHub Actions logs, summarizing failure context, drafting fix plans, and implementing fixes after approval.