/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 via show-me-your-work. Use for /figure-it-out, 'figure it
$ npx -y skills add cursor/plugins --skill figure-it-out --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/figure-it-out
Context preview
The summary Claude sees to decide when to auto-load this skill.
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. Use for /figure-it-out, 'figure it
SKILL.md
figure-it-out.SKILL.mdname: figure-it-out
description: "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. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies."
disable-model-invocation: true
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. 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.
Start
Open a todolist whose first item is to read the Principles section of the **poteto-mode** skill. Then add the phases below as todos.
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). "Done well" has to be checkable.
- Scope, quantified: rough units and effort, plus the blockers grounding surfaced. Raise them before spending hours, not after fifty doomed commits.
- 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 atomic, independently-landable units. Sequence riskiest-unknown-first so option value stays high. 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**) with diverse, isolated, opinionated candidates and a read-only judge on a different model family. 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 genuine 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 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.
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. A blank screenshot passes a lazy gate.
- Pair delegated work with a judge and audit the delegates' artifacts yourself before trusting them. 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, 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.
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, 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.
Read more
name: figure-it-out description: "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. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies." disable-model-invocation: true
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. 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.
Start
Open a todolist whose first item is to read the Principles section of the **poteto-mode** skill. Then add the phases below as todos.
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). "Done well" has to be checkable.
- Scope, quantified: rough units and effort, plus the blockers grounding surfaced. Raise them before spending hours, not after fifty doomed commits.
- 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 atomic, independently-landable units. Sequence riskiest-unknown-first so option value stays high. 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**) with diverse, isolated, opinionated candidates and a read-only judge on a different model family. 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 genuine 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 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.
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. A blank screenshot passes a lazy gate.
- Pair delegated work with a judge and audit the delegates' artifacts yourself before trusting them. 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, 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.
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, 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.
Official Cursor plugins for popular developer tools, frameworks, and SaaS products. Each plugin is a standalone directory at the repository root with its own .cursor-plugin/plugin.json manifest.
Repo: cursor/plugins
Other skills on cursor-plugins.
- /check-agent-compatibility
Run the full repository compatibility pass: scanner score, startup path, validation loop, and docs reliability.
Open skill - /cli-for-agents
Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the
Open skill - /continual-learning
Orchestrate continual learning by delegating transcript mining and AGENTS.md updates to `agents-memory-updater`.
Open skill - /create-plugin-scaffold
Create a new Cursor plugin scaffold with a valid manifest, component directories, and marketplace wiring. Use when starting a new plugin or adding a plugin to a multi-plugin repository.
Open skill - /review-plugin-submission
Audit a Cursor plugin for marketplace readiness. Use when validating manifests, component metadata, discovery paths, and submission quality before publishing.
Open skill - /cursor-sdk
Guide users building apps, scripts, CI pipelines, or automations on top of the Cursor TypeScript SDK (`@cursor/sdk`). Use this skill whenever the user mentions integrating, installing, or writing code against the Cursor SDK; whenever they say `Agent.create`, `Agent.prompt`,
Open skill

