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figure-it-out

Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions. Use for /figure-it-out or 'figure it out'.

日本語の概要は準備中です。原文の説明を表示しています。

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SKILL.md(原文)

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Figure it out

When the task matches no playbook, design one. The deliverable before any code is the workflow itself: a sequence of phases that scales rigor to the task, runs the scientific method, and leaves a decision trail a human can audit after stepping away.

Start

Open a todolist whose first item is to read the shared principles in AGENTS.md. Then add the phases below as todos. Keep intermediate workflow plans, evidence and worker outputs under .agents-state.

Phase A: Frame

Ground first, then commit. Don't start the run until you can state:

  • The definition of done as a falsifiable predicate (the prove-it-works principle skill).
  • Scope, quantified: rough units and effort, plus the blockers grounding surfaced.
  • The rigor level, biased high. One-way doors and high blast radius get more. Reversible low-stakes steps get less. Rigor is gates and artifacts, not "try harder".

Present the framing and tradeoffs before committing to a long run. Reversible work proceeds (the never-block-on-the-human principle skill), but a multi-hour run earns one checkpoint.

Phase B: Design the workflow

Decompose into coherent, independently-landable units. A Haskell unit may span types, instances, generated declarations and their consumers when they form one contract change. For planned migrations with temporary breakage, follow the declared phase boundaries and targeted checks in the outcome-oriented-execution principle skill. Sequence riskiest-unknown-first. Scaffold and verification come before features (the foundational-thinking principle skill).

  • Build the verification harness before the work, with the baseline captured from the pre-change state, so the check reads as "old value vs new value".
  • For one-way-door design decisions, run the architect skill (it runs arena). Skip it for mechanical work whose shape is already concrete. A second arena over a settled design is over-engineering (the minimal-change principle skill).
  • Decide what fans out. Parallelize only across independent seams. Give implementation workers isolated worktrees or checkouts with explicit file ownership; read-only workers can use the shared source with independent outputs. A branch name alone does not isolate filesystem writes. Don't over-fan. Follow the delegation instructions in AGENTS.md.
  • Write the designed phase list down. That list is what the human reviews.

Then execute the design. Add its steps to the todolist as concrete items between the Phase C and Phase D entries. Run each under the Phase C loop discipline, and weave the Phase D log through them, a row as each step lands, rather than saving the whole trail for the end.

Phase C: Run the loop

Each unit is an experiment. State the hypothesis, make the smallest change, measure against the predicate on the real artifact, keep it if it advanced, revert it if it didn't. Apply the sequence-verifiable-units principle skill, verifying each unit before starting the next instead of batching checks at the end.

  • Verify by inspecting the artifact, never a self-report. When something passes too easily, suspect the observation method before the system.
  • Pair delegated work with a judge. If a worker games the gate, reset and harden the contract. If the gate itself is wrong, fix the gate in its own change rather than routing around it.
  • A verdict is VERIFIED, NOT VERIFIED, or INCONCLUSIVE. Inconclusive is not a pass. Don't hide a negative.

Phase D: Keep the audit trail

Log the run via the show-me-your-work skill. figure-it-out's work is usually ambitious enough to commit the trail so the reviewer can read it in the PR. The trail plus the diff is what lets the human come back and trust the work.

Phase E: Verify and hand back

Check the whole against the Phase A predicate on the real product, not just the harness. Encode any recurring correction through a Haskell type, the owning API, a gate, a lint rule, a check, or a script (the encode-lessons-in-structure principle skill).

Reply: the playbook you designed, the rigor level and why, the decision-trail path, what's verified against the predicate, and what's still open.

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