figure-it-out
Skill1 starsChanged 25 days agoMITView on GitHub
Use for a large Pstack migration, an ambitious bespoke run, or work with no fitting playbook.
59 other projects use a version of this, 52 of them edited.
Adopted by
Most recently taken up by
- backnotprop/pstackedited, first seen Nov 15, 2026
- sammyjoyce/prime-pstackedited, first seen Nov 15, 2026
- pronvis/skillsedited, first seen Nov 15, 2026
- upamune/skillsedited, first seen Nov 15, 2026
- mdsmithaustin/pstackedited, first seen Nov 15, 2026
- Yeachan-Heo/oh-my-claude-sisyphustheir own version, first seen Nov 8, 2026
Used with
Projects with it also use setup-pstack, poteto-help and 1 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
bnemaSkillsetup-pstack
Configure which Pi models pstack uses per role. Detects available provider/model specs and writes pstack's user configuration. Use for /setup-pstack, "configure pstack models", or changing pstack model choices.
Also in 25 projects that use this
ianclearySkillpoteto-help
Guides users through pstack setup, /poteto-mode, and picking the skill, playbook, or principle for a task. Type /poteto-help with a question.
Also in 14 projects that use this
JoshueOsunaSkillPoteto Mode
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Also in 3 projects that use this
Other versions59 projects use a version of this.
Word for word · 0
None found.
Edited · 52
- backnotprop/pstack★ 4.2k43% same
- jtaroreh/agystack★ 12833% same
- uzairansaruzi/p3-stack★ 12638% same
- dsebban/skills★ 7142% same
- overextended/skills★ 2235% same
- creedants/pstack-t3★ 1842% same
- painhardcore/pstack★ 1843% same
- Scino/fstack★ 1833% same
- mariusflorescu/pstack-t3★ 1337% same
- adjohn/pstack★ 942% same
42 more not listed
Wrote their own version · 7
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- nmamano/isomux★ 43same name
- TheOnlyFusionCube/potetos-for-everyone★ 21same name
- kinqsradio/orbyn-fullstack-skills★ 4same name
- orbyn-dev/orbyn-fullstack-skills★ 4same name
- requie/endostack★ 4same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository107 other files it gives its agents.
- AGENTS.mdAGENTS.md
- audit-agent-documentationSkill
- automate-meSkill
- babysit-and-shipSkill
- chief-of-staffSkill
- coordinatorSkill
- git-guardrailsSkill
- maintain-skillsSkill
- principlesSkill
- pstack-helpSkill
- pstack-modeSkill
- pstack-setupSkill
- recallSkill
- reflectSkill
- retroSkill
- setup-matt-pocock-skillsSkill
- show-me-your-workSkill
- swarmSkill
- usage-reviewSkill
- wizardSkill
- writing-for-agentsSkill
- broSkill
- in-your-own-wordsSkill
- ketchupSkill
- ketchup-videoSkill
- next-optionsSkill
- prSkill
- reply-shapeSkill
- teachSkill
- technical-writingSkill
- unslopSkill
- write-like-meSkill
- correctSkill
- create-formal-verification-skillSkill
- create-verification-skillSkill
- diagnosing-bugsSkill
- implementSkill
- implement-specSkill
- linting-alignmentSkill
- maintain-formal-verification-skillSkill
- maintain-verification-skillSkill
- make-bot-uiSkill
- pstack-tddSkill
- setup-agent-sign-inSkill
- setup-pre-commitSkill
- setup-ts-deep-modulesSkill
- statechartSkill
- tddSkill
- typescript-best-practicesSkill
- update-dependenciesSkill
- architectSkill
- arenaSkill
- codebase-designSkill
- design-prototypeSkill
- domain-modelingSkill
- grillingSkill
- grill-meSkill
- grill-with-docsSkill
- howSkill
- improve-codebase-architectureSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 59 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
When the task matches no playbook, design one.
“Common” is measured: kept by at least 6 in 10 of the 59 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.
- Ground the goal in repository evidence and invoke /principles for this phase. Invoke /how or /why where needed. State the definition of done as a falsifiable predicate (/principle-prove-it-works); scope, quantified as rough units and effort plus the blockers grounding surfaced; constraints, baseline, and available verification; and 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 (/principle-never-block-on-the-human), but a multi-hour run earns one checkpoint. Complete when the task can be judged by an artifact or observation rather than activity.
- Design the smallest sufficient execution playbook. Decompose into atomic, independently-landable units, sequenced riskiest-unknown-first, with scaffold and verification before features (/principle-foundational-thinking). 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". Run /architect, which runs /arena, for one-way-door design decisions; skip them for mechanical work whose shape is already concrete; a second arena over a settled design is over-engineering (/principle-laziness-protocol). Parallelize only across seams, giving each worker its own worktree or branch (/principle-separate-before-serializing-shared-state), and don't over-fan. Write down the phases, units, hypotheses, acceptance gates, rollback or rejection conditions, and reporting; that list is what the human reviews. Complete when every phase ends with checkable evidence and the run fits its grant and budget.
- Run the loop, using /swarm for independent work and critics. 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. Verify each unit before starting the next (/principle-sequence-verifiable-units). 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. A verdict is VERIFIED, NOT VERIFIED, or INCONCLUSIVE; inconclusive is not a pass. Don't hide a negative. Complete each unit only when its actual behavior is proved.
- Keep the decision trail through /show-me-your-work, a row as each step lands rather than the whole trail at the end. This work is usually ambitious enough to commit the trail so the reviewer can read it in the PR. Replan from evidence, preserving scope and approved-interface gates. A productive run still respects its agreed time limit. Complete each checkpoint when progress, remaining work, and decisions are durable.
- Check the whole against the step 1 predicate on the real product, not just the harness. Encode any recurring correction as a gate, a lint rule, a check, or a script (/principle-encode-lessons-in-structure). Return the playbook you designed, the rigor level and why, the decision-trail path, the predicate result and evidence, alternatives, and exact gaps. Use /ketchup to explain the user-facing result. Complete when the goal is demonstrated or unfinished work has a concrete handoff; effort alone never establishes completion.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

