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 agent-conductgit 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/agent-conduct)<a href="https://agentmods.dev/skills/github/gh-aw/agent-conduct"><img src="https://agentmods.dev/badge/skills/github/gh-aw/agent-conduct/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/agent-conduct"><img src="https://agentmods.dev/badge/skills/github/gh-aw/agent-conduct.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 | $0.00012 | $0.00293 |
| Opus 5.5 | $0.00005 | $0.00117 |
| Sonnet 5.5 | $0.00002 | $0.00059 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
agent-conduct 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 48 lines differ
- agent-conduct — 100% identical, 0 lines differ
- agent-conduct — 100% identical, 0 lines differ
What it actually says
Context
Every squad agent must follow these two hard rules. They were previously duplicated in every charter. Now they live here as a shared skill, loaded once.
Patterns
Product Isolation Rule (hard rule)
Tests, CI workflows, and product code must NEVER depend on specific agent names from any particular squad. "Our squad" must not impact "the squad." No hardcoded references to agent names (Flight, EECOM, FIDO, etc.) in test assertions, CI configs, or product logic. Use generic/parameterized values. If a test needs agent names, use obviously-fake test fixtures (e.g., "test-agent-1", "TestBot").
Peer Quality Check (hard rule)
Before finishing work, verify your changes don't break existing tests. Run the test suite for files you touched. If CI has been failing, check your changes aren't contributing to the problem. When you learn from mistakes, update your history.md.
Anti-Patterns
- Don't hardcode dev team agent names in product code or tests
- Don't skip test verification before declaring work done
- Don't ignore pre-existing CI failures that your changes may worsen
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 · 25 lines · 12 tokens per session scan A 898443cfbdd1
agent-conduct is a skill published in the GitHub repository github/gh-aw (5,435 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 293 once invoked, about $0.0000 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 2026-09-03.
Other skills, from other repositories
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.
deploy
Use when ready to ship — runs pre-push gates (lint, typecheck, build, tests, security sweep), commits, releases, and pushes. Standalone, never auto-invoked. Push always requires explicit confirmation. Trigger with /hyperflow:deploy, "ship it", "ready to push", "release", "cut a release", "deploy".
codspeed-optimize
Autonomously optimize code for performance using CodSpeed benchmarks, flamegraph analysis, and iterative improvement. Use this skill whenever the user wants to make code faster, reduce CPU usage, optimize memory, improve throughput, find performance bottlenecks, or asks to 'optimize', 'speed up', 'make faster'…
codspeed-setup-harness
Set up performance benchmarks and CodSpeed harness for a project. Use this skill whenever the user wants to create benchmarks, add performance tests, set up CodSpeed, configure codspeed.yml, integrate a benchmarking framework (criterion, divan, pytest-benchmark, vitest bench, go test -bench, google benchmark), or when…
e2e-testing
Use when writing or stabilizing Playwright tests that drive a real browser through multi-step journeys — durable locators, web-first assertions, storageState auth, trace/retries, and flakes that only bite in CI. NOT in-process component tests (that is testing-web), NOT WCAG auditing (that is accessibility), NOT the…
AI Release Guardian
Analyze a git diff, map affected risks, select the tests that matter, detect coverage gaps on changed lines, run configurable quality gates, and produce a go/no-go release report with cited evidence. Recommends only; never merges or deploys.