write-spec

Write Spec

Turn a large feature into a ladder of small contracts. Each rung should be understandable to the human, testable by an agent, and useful before the whole feature is done.

First Principles

1. Grill before planning. Ask one question at a time until you know the desired outcome, non-goals, review surface, sacred contracts, missing assets, and first useful playable checkpoint. Give your recommended answer with each question so the user can accept, reject, or edit it. Inspect the repo instead of asking questions the code can answer. Close the interview by asking whether the plan must carry backward compatibility or data migrations — the default is neither: hard cutovers, no compat shims, no migration scaffolding, no deploy-order dances. Only the user opting in puts them in the plan.

2. Slice at API seams. Each slice should behave like a tiny library where possible: named module boundary, typed inputs/outputs, deterministic fixtures, and tests at the seam. If a slice needs three unrelated systems booted before it can be checked, sharpen the seam.

3. Research the fog. When the feature depends on an unfamiliar domain, high-fidelity visual target, named reference, benchmark, external repo, library, or "how do people usually do this?" question, do targeted online research before finalizing slices. Prefer primary sources: official docs, source repos, papers, case studies, talks, and shipped examples. If a reference implementation exists, add a replication spike before translation or approximation.

4. Make progress visible. For visual or interactive work, every slice should produce something playable: a route, fixture page, harness, CLI probe, or HTML visualization the human can run, inspect, screenshot, and critique. Tests prove contracts; demos expose taste and intent.

5. Optimize feedback loops. Slice so the next useful question can be answered quickly. Prefer tiny runnable surfaces, hot-reloadable harnesses, sample fixtures, and self-contained workbenches over plans that require the whole feature to exist before anyone can learn from it. For asset-heavy work, plan an asset app/workbench where humans and artists can add samples, upload replacements, preview them live, and see validation failures fast.