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 agentmods add skills/github/gh-aw/squad-commandsnpx skills add github/gh-aw --skill squad-commandsgit 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/squad-commands)<a href="https://agentmods.dev/skills/github/gh-aw/squad-commands"><img src="https://agentmods.dev/badge/skills/github/gh-aw/squad-commands.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 | $0.00034 | $0.02641 |
| Opus 5 | $0.00017 | $0.01321 |
| Sonnet 5 | $0.00007 | $0.00528 |
| Haiku 4.5 | $0.00003 | $0.00264 |
Grade A, and why
squad-commands 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 yesterday.
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
7 near-identical copies found in the catalogue:
- squad-commands — 100% identical, 0 lines differ
- squad-commands — 100% identical, 0 lines differ
- squad-commands — 100% identical, 0 lines differ
- squad-commands — 97% identical, 6 lines differ
- squad — 89% identical, 26 lines differ
- squad — 88% identical, 20 lines differ
- squad — 88% identical, 20 lines differ
How it starts
The opening of the file, as written. The whole thing — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Menu Presentation Rules
When the user triggers this skill ("squad commands", "help", "what can squad do", etc.):
- Category-level menu first. Present category names as an
ask_userchoice list:📋 Squad Commands — pick a category: 1. Install & Upgrade 2. Team Management 3. Issues & PRs 4. Plugins & Skills 5. Model & Cost 6. Sessions & State - Drill-down. After selection, show operation titles in that category as a second
ask_userlist. - Direct match skips the menu. If the user says "how do I upgrade with state backend," match to the specific entry and go straight to argument collection.
- Compact fallback. If
ask_useris unavailable, render as a markdown table instead. - Back / Cancel. Include "← Back to categories" in sub-menus. Include "Cancel" in confirmation prompts. Respect "never mind" / "cancel" at any point.
Argument collection: For entries with args, iterate the list sequentially. Use ask_user with choices when choices is provided; free-text prompt otherwise. If the user says "just do it" or "defaults are fine," skip remaining args and use their defaults.
Confirmation template:
⚠️ This will {action-description}.
{what will change}
Proceed? (yes / no)
Install & Upgrade
Upgrade Squad CLI
- intent: upgrade squad, update squad, install latest version, get new version
- summary: Upgrade Squad CLI to the latest version for your channel
- action: shell
- command: squad upgrade
- args:
state-backend: Which state backend? | choices: {worktree, git-notes, orphan, two-layer} | default: (keep current)
- confirm: false
- platform_caveats: Requires terminal. In VS Code, open the integrated terminal and run the command directly.
Initialize Squad
- intent: set up squad, initialize squad, create team, start squad in this project
- summary: Scaffold Squad in the current directory (idempotent)
- action: shell
- command: squad init
- args: (none)
- confirm: false
- platform_caveats: Requires terminal. Recommend a standalone terminal for best results.
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.
- yesterday First seen · 304 lines · 34 tokens per session scan A 4e7ea9b948ba
squad-commands is a skill published in the GitHub repository github/gh-aw (5,091 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 2,641 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 2026-09-03.
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Completion-safe bucketing for Helix work items with nullable exit codes.
watch-pr
Watch a GitHub pull request for CI status, reviews, comments, merge conflicts, and terminal states using the gh-watch extension. Use when the user wants to monitor a PR, wait for CI, or track PR progress.