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.
Borrowing it
Nothing to install: this file belongs to github/gh-aw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/github/gh-aw/main/.github/skills/custom-engine-implementation/SKILL.mdgit 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/custom-engine-implementation)<a href="https://agentmods.dev/skills/github/gh-aw/custom-engine-implementation"><img src="https://agentmods.dev/badge/skills/github/gh-aw/custom-engine-implementation/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/custom-engine-implementation"><img src="https://agentmods.dev/badge/skills/github/gh-aw/custom-engine-implementation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 104 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00026 | $0.01561 |
| Opus 5.5 | $0.00010 | $0.00624 |
| Sonnet 5.5 | $0.00005 | $0.00312 |
| Haiku 4.5 | $0.00003 | $0.00156 |
Grade A, and why
custom-engine-implementation 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 23d 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.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Custom Engine Implementation
Use this skill when adding a new agentic engine definition or extending the behavior-defined engine infrastructure.
Choose the smallest implementation
Prefer a shared Markdown engine definition. Installation, execution, MCP
configuration, provider routing, caching, manifests, plugins, network defaults,
harness scripts, and log parsing can already be declared through
engine.behaviors.
Only change Go code when the engine needs a reusable behavior that the declarative model cannot express. Add a dedicated Go engine only when the shared behavior-defined runtime cannot run the engine at all.
| Need | Implementation |
|---|---|
| Existing behaviors are sufficient | Add an imported shared engine definition |
| A reusable declarative behavior is missing | Extend the definition model and behavior-defined runtime |
| The shared runtime is fundamentally unsuitable | Add a dedicated Go engine and register it |
The relevant implementation is in:
pkg/workflow/engine_definition.gofor the definition model and catalogpkg/workflow/behavior_defined_engine.gofor the shared runtimepkg/workflow/engine_definition_loader.gofor embedded built-in definitionspkg/workflow/agentic_engine.gofor dedicated Go engine registrationpkg/parser/schemas/main_workflow_schema.jsonfor the workflow schema
Study representative engines
Read the closest examples before making changes:
.github/workflows/shared/opencode.md: npm installation, merged configuration, MCP, provider routing, and log parsing.github/workflows/shared/aider.md: Python installation and a custom harness without native MCP.github/workflows/shared/crush.md: native MCP configuration adapter and harness.github/workflows/shared/cursor.md: plugin support.github/workflows/shared/deepseek-harness.md: provider endpoint discovery and a headless profile
Use the examples to identify a pattern, not as a reason to copy optional behaviors.
Add a shared engine definition
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.
- 23d ago Changed 0489974b76a5
- 1mo ago First seen · 187 lines · 26 tokens per session scan A 14e5142a7726
custom-engine-implementation is a skill published in the GitHub repository github/gh-aw (5,406 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 1,561 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
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.