Harness Engineering

Transform any code project so AI agents can work in it reliably and autonomously.

The bottleneck is never the agent's coding ability — it's the environment the agent operates in. This skill builds that environment.

Core Principles

These govern every decision:

1. Declarative over procedural — Define what "correct" looks like (verification criteria), not step-by-step procedures. Agents determine how to verify on their own and generate temporary scripts if needed.

2. Recognition over recall — Extract knowledge by showing users detected patterns and asking them to react (choose, confirm, reject). Never ask open-ended "describe your principles" questions.

3. Minimal context footprint — Every generated document must be as concise as possible. Agents read actual code for details. Only externalize knowledge that CANNOT be inferred from code: architectural rules, canonical pattern choices, prohibited actions, business domain terms.

4. Persist invariants, not procedures — Commit architectural rules, lint configs, structural tests (permanent invariants). Never commit task-specific verification scripts — agents create those on-the-fly per task and discard them after.

5. Language-agnostic — Adapt to the project's tech stack. Never assume a specific language, framework, or toolchain.