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](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.

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.