custom-engine-implementation

A guide for adding new agent engines to gh-aw, a GitHub tool for running automated workflows, using written behavior definitions and Go code when needed.

In plain words
What is it for?
Use it to add engine definitions, extend the behavior system, or register a dedicated Go engine when the shared runtime cannot support one.
Why use it?
It helps developers choose whether an engine can be declared in shared configuration or requires changes to the Go implementation.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/github/gh-aw/custom-engine-implementation
Any agent
npx skills add github/gh-aw --skill custom-engine-implementation
Clone the repo
git clone --depth 1 https://github.com/github/gh-aw

Made for: Claude Code, Codex.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,560 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.01560
Opus 5 $0.00013 $0.00780
Sonnet 5 $0.00005 $0.00312
Haiku 4.5 $0.00003 $0.00156

Measured 2d ago against content hash 14e5142a7726, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

.github/skills/custom-engine-implementation/SKILL.md · 187 lines

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.go for the definition model and catalog
  • pkg/workflow/behavior_defined_engine.go for the shared runtime
  • pkg/workflow/engine_definition_loader.go for embedded built-in definitions
  • pkg/workflow/agentic_engine.go for dedicated Go engine registration
  • pkg/parser/schemas/main_workflow_schema.json for 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

Read the full file on GitHub · 187 lines

Changes

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.

  1. 2d ago First seen · 187 lines · 26 tokens per session scan A 14e5142a7726

Subscribe to this mod's changes

custom-engine-implementation is a skill published in the GitHub repository github/gh-aw (5,050 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 1,560 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 2026-08-30.

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