About figure-it-out
figure-it-out is an agent skill for designing and running a task-specific workflow when no existing playbook fits. It guides agents to frame scope and rigor, verify work in small units, and leave an auditable decision trail.
Key features
- 01Task framing and scope estimates
- 02Rigor selection by risk
- 03Workflow design and sequencing
- 04Incremental experiment-and-verify loop
- 05Decision trail and handoff
Use cases
- 01Planning work without a matching playbook
- 02Breaking a complex task into verified units
- 03Recording decisions for reviewer handoff
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ mdsmithaustin/ pstack --skill figure-it-outAfter installing, type/figure-it-outin Claude Code to confirm it loaded.
Bundled filesagents/openai.yaml
Details
From the project READMEFigure 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 worklist whose first item is to read the Principles section of the poteto-mode skill. Then add the phases below as items.
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).
- A
worth doingorwon't doverdict for each requested item, with a brief reason tied to the project's design and the user's goal. Make these calls before sizing. A fit judgment does not cancel an explicit requirement. Record proposed exclusions and authorized scope changes separately. - Scope, quantified for the accepted items. Size compared options on the same basis, including implementation, tests, documentation, generated files, and verification effort. Name exclusions and uncertainty, 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".
Track actual scope and effort against these estimates. When the chosen option exceeds a rejected option's comparable estimate, reassess the choice and report the overrun. Under an autonomy grant, continue within that grant unless an existing gate requires the operator.
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 atomic, independently-landable units. 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, use 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 laziness-protocol principle skill).
- Decide what fans out. Parallelize only across seams, and give each worker its own worktree or branch (the separate-before-serializing-shared-state principle skill). Don't over-fan.
- Write the designed phase list down. That list is what the human reviews.
Then execute the design. Add its steps to the worklist 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. Use the principle-sequence-verifiable-units skill. Verify 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.
- For each new regression test, report the behavior it protects and evidence that it fails on the relevant defect before the fix and passes after it. A parent revision, safe targeted mutation, or failing fixture can supply the defect. Keep mutations in a disposable checkout. A setup or compiler failure does not prove the intended behavior failed. Reuse one run when it covers several tests. For other new tests, state the independent oracle and a plausible defect the test rejects. If a failing run is unsafe or unavailable, record the gap instead of claiming regression proof.
- A verdict is VERIFIED, NOT VERIFIED, or INCONCLUSIVE. Inconclusive is not a pass. Don't hide a negative.
Phase D: Keep the audit trail
Use the show-me-your-work skill to log the run. Let that skill choose whether the trail stays local or is committed. Keep durable completion evidence available to the reviewer.
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 as a gate, a lint rule, a check, or a script (the encode-lessons-in-structure principle skill).
Before handoff, link unresolved material defects and unmet requirements to existing tracker items or a checked-in known-issues file. Create missing records when authorized. Include the impact, evidence, current disposition, and owner when known. Filing a blocker does not satisfy the done predicate. If filing is unavailable or unauthorized, name that gap and the retained record.
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.