ECL Harness Engineer
Design and create Harness Engineering infrastructure so AI agents can work reliably in a codebase.
Core Philosophy: "Intelligence without infrastructure is just a demo." The Agent Harness is the Operating System — the LLM is just the CPU. The repository becomes the single source of truth — if an agent can't see it in context, it doesn't exist.
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
When to Use This Skill
- Use when a repository needs AI-agent collaboration infrastructure such as
AGENTS.md, docs/ECL.md, docs/STATUS.md, harness change tracking, or mechanical validation gates.
- Use when auditing an existing Agent Harness for missing ECL lifecycle docs, change templates, lint checks, environment contracts, or CI integration.
- Use when converting repeated agent workflow failures into repository-local documentation, tests, lint rules, or lightweight auto-evolution checks.
- Do not use for ordinary business feature implementation unless the requested work is specifically about creating or improving the repository harness.
Limitations
- This skill creates or audits harness infrastructure; it does not replace product requirements, implementation planning, code review, or release approval for the target project.
- The generated ECL docs, linters, scripts, and CI examples must be adapted to the repository's actual stack, security model, and existing contributor workflow before enforcement.
- Auto-evolve recommendations are guidance only. Apply harness changes through normal review, validation, and rollback discipline instead of accepting them as autonomous policy changes.
1---2name: ecl-harness-engineer3description: Create or audit ECL Agent Harness infrastructure: AGENTS.md, change tracking, repository guidance, lint checks, CI gates, and agent handoff docs.4license: MIT5---67# ECL Harness Engineer8Design and create Harness Engineering infrastructure so AI agents can work reliably in a codebase.910> **Core Philosophy**: "Intelligence without infrastructure is just a demo." The Agent Harness is the Operating System — the LLM is just the CPU. The repository becomes the single source of truth — if an agent can't see it in context, it doesn't exist.1112## Detailed Guide1314Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.1516## When to Use This Skill1718- Use when a repository needs AI-agent collaboration infrastructure such as `AGENTS.md`, `docs/ECL.md`, `docs/STATUS.md`, harness change tracking, or mechanical validation gates.19- Use when auditing an existing Agent Harness for missing ECL lifecycle docs, change templates, lint checks, environment contracts, or CI integration.20- Use when converting repeated agent workflow failures into repository-local documentation, tests, lint rules, or lightweight auto-evolution checks.21- Do not use for ordinary business feature implementation unless the requested work is specifically about creating or improving the repository harness.2223## Limitations2425- This skill creates or audits harness infrastructure; it does not replace product requirements, implementation planning, code review, or release approval for the target project.26- The generated ECL docs, linters, scripts, and CI examples must be adapted to the repository's actual stack, security model, and existing contributor workflow before enforcement.27- Auto-evolve recommendations are guidance only. Apply harness changes through normal review, validation, and rollback discipline instead of accepting them as autonomous policy changes.
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