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/client-compatibilitynpx skills add github/gh-aw --skill client-compatibilitygit 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/client-compatibility)<a href="https://agentmods.dev/skills/github/gh-aw/client-compatibility"><img src="https://agentmods.dev/badge/skills/github/gh-aw/client-compatibility.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 | $0.00018 | $0.01238 |
| Opus 5 | $0.00009 | $0.00619 |
| Sonnet 5 | $0.00004 | $0.00248 |
| Haiku 4.5 | $0.00002 | $0.00124 |
Grade A, and why
client-compatibility 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
8 near-identical copies found in the catalogue:
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 178 lines differ
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 0 lines differ
- client-compatibility — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
Squad runs on multiple Copilot surfaces (CLI, VS Code, JetBrains, GitHub.com). The coordinator must detect its platform and adapt spawning behavior accordingly. Different tools are available on different platforms, requiring conditional logic for agent spawning, SQL usage, and response timing.
Patterns
Platform Detection
Before spawning agents, determine the platform by checking available tools:
-
CLI mode —
tasktool is available → full spawning control. Usetaskwithagent_type,mode,model,description,promptparameters. Collect results viaread_agent. -
VS Code mode —
runSubagentoragenttool is available → conditional behavior. UserunSubagentwith the task prompt. Dropagent_type,mode, andmodelparameters. Multiple subagents in one turn run concurrently (equivalent to background mode). Results return automatically — noread_agentneeded. -
Fallback mode — neither
tasknorrunSubagent/agentavailable → work inline. Do not apologize or explain the limitation. Execute the task directly.
If both task and runSubagent are available, prefer task (richer parameter surface).
VS Code Spawn Adaptations
When in VS Code mode, the coordinator changes behavior in these ways:
- Spawning tool: Use
runSubagentinstead oftask. The prompt is the only required parameter — pass the full agent prompt (charter, identity, task, hygiene, response order) exactly as you would on CLI. - Parallelism: Spawn ALL concurrent agents in a SINGLE turn. They run in parallel automatically. This replaces
mode: "background"+read_agentpolling. - Model selection: Accept the session model. Do NOT attempt per-spawn model selection or fallback chains — they only work on CLI. In Phase 1, all subagents use whatever model the user selected in VS Code's model picker.
- Scribe: Cannot fire-and-forget. Batch Scribe as the LAST subagent in any parallel group. Scribe is light work (file ops only), so the blocking is tolerable.
- Launch table: Skip it. Results arrive with the response, not separately. By the time the coordinator speaks, the work is already done.
read_agent: Skip entirely. Results return automatically when subagents complete.agent_type: Drop it. All VS Code subagents have full tool access by default. Subagents inherit the parent's tools.description: Drop it. The agent name is already in the prompt.- Prompt content: Keep ALL prompt structure — charter, identity, task, hygiene, response order blocks are surface-independent.
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 · 90 lines · 18 tokens per session scan A d8da5e1e9918
client-compatibility is a skill published in the GitHub repository github/gh-aw (5,104 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,238 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
c-github
Interact with GitHub using the gh CLI and jq. Manage PRs, issues, repositories, and Actions workflows. Make raw API calls with gh api for anything not covered by built-in commands.
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.
watch-tag
Watch a GitHub repository for new tags using the gh-watch extension. Use when the user wants to be notified when a tag is created, when a release is cut, or when a tag that includes a specific commit appears (e.g. "tell me when my merge ships in a release").
watch-branch
Watch a GitHub branch for new commits using the gh-watch extension. Use when the user wants to be notified when new commits are pushed to a branch, monitor main for merges, or track branch activity.
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.
update-architecture-docs
Generate or update the architecture documentation in docs/content/architecture/. Use on "update architecture docs", "generate architecture documentation", "regenerate architecture docs", or after any structural change to the codebase.