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 via show-me-your-work.
npx -y skills add cursor/plugins --skill figure-it-out --agent claude-codeInstalls into .claude/skills of the current project.
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. Bias toward more rigor. The cost of building the wrong thing dwarfs the cost of being careful.
Don't reinvent a playbook you already have. A focused single-unit task that matches Bug fix, Perf, Feature, Visual parity, Eval, or Multi-phase plan routes there. But a large or cross-cutting version of one (a migration across many call sites, an ambitious multi-part change), or work the user reviews after stepping away, belongs here even though a single-unit version would be a Feature. The rigor and the audit trail are the point.
Open a todolist whose first item is to read the Principles section of the poteto-mode skill. Then add the phases below as todos.
Ground first, then commit. Don't start the run until you can state:
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.
Decompose into atomic, independently-landable units. Sequence riskiest-unknown-first so option value stays high. Scaffold and verification come before features (the foundational-thinking principle skill).
Then put the design into motion. Add its steps to the todolist as concrete items, after the Phase C entry and before Phase D. 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.
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.
Log the run via the show-me-your-work skill, one canonical TSV with a row per decision and per unit, evidence as links. figure-it-out's work is usually ambitious enough to commit the trail so the reviewer can read it in the PR; commit it when confidence has to be shown. Prefer evidence produced by committed scripts so a reviewer can re-run it. The trail plus the diff is what lets the human come back and trust the work.
Check the whole against the Phase A predicate on the real product, not just the harness. Encode any recurring correction as a gate, a lint rule, a check, or a script, so the win can't silently regress (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.
sickn33/antigravity-awesome-skills