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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.
Passed 9 of 16 test cases with the skill, and 9 of 16 without it.
and 3 more in the full report
4 fixed8 passed either way6 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
When evaluating an experimental trial unit in Phase C of a complex workflow, what are the allowed verdict classifications?
| Checked | Without skill | With skill |
|---|---|---|
| Classifies verdicts strictly as VERIFIED, NOT VERIFIED, or INCONCLUSIVE | Missed | Passed |
The instructions your model reads when the skill loads.
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.
test cases passed, vs 9 / 16 without
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