fable-plan — write the plan before you build it (hard multi-step only)

This skill turns a measured result into an action. In a controlled A/B (eval/technique-ab/run-plan-first.mjs, GPT-5.5-judged, n=12 on deliberately hard 5-part tasks), externalizing a numbered plan before executing beat diving straight to the deliverable 9–1 of 10 decided (90%, p=0.0215). On hard multi-step work, the plan-first deliverable was better organized and more correct. The cost is one short planning pass — so this is only worth it when the task is genuinely hard.

Your job: surface the plan as a short artifact the work then follows — don't pad a simple task with ceremony.

When NOT to use this (this bound is the whole point)

• A single-file change, a one-step fix, a question, or anything you can do correctly in one pass → just do it. A plan here is pure overhead — the A/B win was on hard 5-part tasks, and an A/B on routing found always-planning adds length without quality on simple work.
• You haven't read the relevant code yet → read enough to plan against reality, not a guess.

Procedure

1. Confirm it's hard enough. Roughly four or more distinct parts, multiple files, or real ordering / dependency between steps. If not, skip this skill.
2. Write a short numbered plan first — the parts in order, each one a concrete step with its target outcome and (where it matters) what it depends on. Keep it tight: one line per step, not an essay.
3. Name the risky or uncertain steps — the one or two places most likely to be wrong, and the check that will tell you. This is where plan-first pays off: you catch ordering/coverage gaps before building.
4. Execute against the plan, in order. If reality diverges, update the plan line rather than silently drifting — the plan stays the spec you're building to.
5. Close each part with its check. A step isn't done until the thing that proves it (a test, a diff against the spec, a run) passes — ground completion in evidence, not in "looks right."

Expected output

A short numbered plan up front, then the deliverable built against it, with each part's check shown. The plan is a means, not the deliverable — keep it proportional to the task.

Honest bound

The A/B measured a forced-choice quality preference on hard 5-part tasks; it does not show plan-first helps on simple work (it doesn't — that's why this skill is trigger-gated), and it is a one-shot quality result, not a multi-session or productivity number. Use it where the task is actually hard.