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 workflow-step-summariesgit 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/workflow-step-summaries)<a href="https://agentmods.dev/skills/github/gh-aw/workflow-step-summaries"><img src="https://agentmods.dev/badge/skills/github/gh-aw/workflow-step-summaries.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.00268 |
| Opus 5 | $0.00009 | $0.00134 |
| Sonnet 5 | $0.00003 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
workflow-step-summaries 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 3d 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 Actions Step Summary Guidance
Use this skill when generating content for $GITHUB_STEP_SUMMARY.
Structure summaries for quick scanning
- Start sections at
###(h3) for readable hierarchy in workflow run pages. - Keep titles plain text with no emojis.
- Put the most important status and outcomes first.
Use progressive disclosure
- Wrap detailed diagnostics, logs, and secondary data in HTML
<details>blocks. - Use a concise
<summary>line that states what the collapsed section contains. - Keep default-expanded content short; move verbose output into collapsible blocks.
Use Markdown for code and review output
- In
actions/github-script, prefercore.summary.*helpers to build summary content. - Use inline code with backticks for commands, paths, IDs, and config keys.
- Use fenced code blocks with a language tag for logs, diffs, snippets, or commands.
- Present review findings as markdown sections with clear severity and action items.
Suggested checklist before writing
- Confirm section headings start at h3.
- Confirm no title includes emoji.
- Confirm verbose content is inside
<details>blocks. - Confirm code and review content uses proper markdown code formatting.
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.
- 3d ago First seen · 35 lines · 17 tokens per session scan A 1b69fd73bbb7
workflow-step-summaries is a skill published in the GitHub repository github/gh-aw (5,108 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 268 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.
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.
ci-debug
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for…
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.