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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 18 of 19 test cases with the skill, and 13 of 19 without it.
and 7 more in the full report
6 fixed12 passed either way0 still failing1 broke4 errored
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
When constructing the task list for an unscripted zero-downtime database index rebuild, where should the concrete execution steps designed in Phase B be placed in the todolist?
| Checked | Without skill | With skill |
|---|---|---|
| Inserts designed execution steps after Phase C entry and before Phase D | 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.
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. Scaffold and verification come before features (the foundational-thinking principle skill).
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.
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. 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.
test cases passed, vs 13 / 19 without
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