how
Skill2 starsChanged 3 months agoMITView on GitHub
Use for \"how does X work\", code walkthroughs before changing something, and placement / ownership / layering questions (\"where should this live\", \"which package owns this\", \"is this the right layer\"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique architecture. Use why for motivation.
We split this skill into the rules it gives an agent
10 rules. 0 are common, 6 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 75 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
When in doubt, lean simple.
- Very specific: line 45
Call pstack_task once with one entry per explorer in its tasks array:
- Very specific: line 52
Start broad: Glob for relevant directories, Grep for key types/interfaces/class names
- Distinctive: line 53
Follow the thread: from an entry point, trace the call chain (callers, callees, data flow, type definitions)
- Distinctive: line 54
Read the actual code, don't guess from file names
- Distinctive: line 55
Stop when it can describe the full path from input to output (or trigger to effect) without hand-waving any step
- Distinctive: line 90
Follow this structure, adapted to the question.
- Distinctive: line 108
Run the full explain flow above (Steps 1-4).
- Very specific: line 112
After the explanation is complete, call pstack_task once with one critic per entry in the configured how-critics list.
- Very specific: line 119
Read references/critic-prompt.md for the prompt template.
“Common” is measured: kept by at least 6 in 10 of the 75 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
How
Explore the codebase to answer "how does X work?" questions. Produce clear architectural explanations at the level of a senior engineer onboarding onto a subsystem. Enough to build a working mental model, not annotated source code.
Two modes:
- Explain (default). Explore the codebase and produce a clear explanation
- Critique. Explain first, then spawn multiple models to independently identify architectural issues
Explain Mode
Step 1. Understand the Question and Assess Complexity
Parse what the user is asking about:
- "How does the rate limiter work?", a subsystem
- "How do we handle billing for on-demand usage?", a feature flow
- "How is the auth service structured?", an architectural overview
- "Walk me through what happens when a user submits a form", a runtime trace
Identify the scope. If ambiguous, state your best-guess interpretation before exploring. Don't ask. Let the user redirect if you're off.
Assess complexity to decide the approach:
- Simple (a single module, a small utility, a narrow question like "how does function X work"): skip explorer agents; the explainer explores and explains in a single pass. Go to Step 2b.
- Complex (a subsystem spanning multiple files/services, a cross-cutting feature, a full architectural overview): spawn parallel explorer agents first, then hand off to the explainer. Go to Step 2a.
When in doubt, lean simple. You can always spawn explorers if the explainer hits a wall.
Step 2a. Explore (complex questions only)
Decompose the question into 2-4 parallel exploration angles, each a distinct slice of the subsystem so explorers don't duplicate work. Example split for "how does the rate limiter work?":
- Explorer 1: data model and state management
- Explorer 2: request path and enforcement
- Explorer 3: configuration and metrics infrastructure
The right decomposition depends on the question. Use your judgment. Narrow questions: 2 explorers is fine. Broad subsystems: up to 4.
Call pstack_task once with one entry per explorer in its tasks array:
poteto:falsemodel: configured how-explorer model, otherwiseinherit-parenttools:["read", "grep", "find", "ls"]
Each explorer gets the same base prompt from references/explorer-prompt.md plus a specific exploration angle naming its slice. Each explorer should:
- Start broad: Glob for relevant directories, Grep for key types/interfaces/class names
- Follow the thread: from an entry point, trace the call chain (callers, callees, data flow, type definitions)
- Read the actual code, don't guess from file names
- Stop when it can describe the full path from input to output (or trigger to effect) without hand-waving any step
- Note things that are surprising, non-obvious, or that a newcomer would get wrong
Each explorer returns structured findings: components found, flow traced, files read, anything non-obvious. Overlap between explorers is fine; the explainer reconciles.
Then proceed to Step 3.
Step 2b. Direct Explain (simple questions)
Spawn a single pstack child agent that explores and explains in one pass:
poteto:falsemodel: configured how-explainer model, otherwiseinherit-parenttools:["read", "grep", "find", "ls"]
The agent does its own exploration (Glob, Grep, Read) and writes the explanation directly. Read references/explainer-prompt.md for the communication style and output format. Same structure, just no explorer findings as input.
Proceed to Step 4.
Step 3. Synthesize (complex questions only)
Once all explorers return, spawn a single pstack child agent to synthesize their findings into one coherent explanation:
poteto:falsemodel: configured how-explainer model, otherwiseinherit-parenttools:["read", "grep", "find", "ls"]
The explainer gets all explorers' findings and writes the human-facing explanation (output format below). Read references/explainer-prompt.md for the full prompt template. The explainer reconciles overlapping findings, resolves contradictions, and weaves the slices into a unified picture.
Step 4. Present
Present the explainer's output to the user. You may lightly edit for clarity or add context from the conversation, but don't substantially rewrite. The explainer's communication is the product.
Output Format
Follow this structure, adapted to the question. Not every section is needed for every question.
Overview. 1-2 paragraphs. What it is, what it does, why it exists. Enough to decide whether to keep reading.
Key Concepts. The important types, services, or abstractions. Brief definition of each. Not exhaustive, just the ones needed to understand the rest.
How It Works. The core of the explanation. Walk through the flow: what triggers it, what happens step by step, where data goes, the decision points. Prose, not pseudocode. Reference specific files and functions so the reader can go look, but don't dump code blocks unless a snippet is genuinely necessary.
Where Things Live. A brief map of the relevant files/directories. Not every file, just the ones needed to start working in this area.
Gotchas. Non-obvious or surprising things that would trip someone up. Historical context that explains why something looks weird. Known sharp edges.
Critique Mode
Triggered when the user asks for architectural issues, problems, or improvements, not just understanding.
Step 1. Explain First
Run the full explain flow above (Steps 1-4). You must understand the architecture before critiquing it.
Step 2. Spawn Critics
After the explanation is complete, call pstack_task once with one critic per entry in the configured how-critics list. When no list exists, use one inherit-parent critic. A configured multi-provider list supplies model diversity.
For each critic:
poteto:falsemodel: one model from the configured how-critics list, orinherit-parent.tools:["read", "grep", "find", "ls"]
Read references/critic-prompt.md for the prompt template. Each critic gets:
- The explanation from Step 1 (so they don't re-explore)
- The relevant file paths (so they can read the actual code)
- The architectural critique rubric from
references/critique-rubric.md
Step 3. Lead Judgment
Same framework as the interrogate skill. You're a pragmatic lead, not an aggregator.
Categorize findings:
- Act on. Architectural problems worth fixing now
- Consider. Real concerns, but the cost/benefit is unclear
- Noted. Valid observations, low priority
- Dismissed. Wrong, missing context, or style preference
Present the explanation first (from Step 1), then the critique verdict below it. The explanation should stand on its own; someone who just wants to understand the system shouldn't wade through critique.
Other versions76 projects use a version of this.
Word for word · 0
None found.
Edited · 54
- backnotprop/pstack★ 2.7k17% same
- poteto/how★ 87856% same
- jtaroreh/agystack★ 12817% same
- uzairansaruzi/p3-stack★ 12632% same
- Dimon94/dverity★ 10733% same
- Dimon94/skills★ 10733% same
- dsebban/skills★ 7117% same
- roerohan/skills★ 2987% same
- Scino/fstack★ 1882% same
- kkgogogo17/pi-pstack★ 989% same
44 more not listed
Wrote their own version · 22
- overextended/skills★ 18same name
- sirius-cc-wu/sirius-skills★ 5same name
- TheOnlyFusionCube/potetos-for-everyone★ 5same name
- painhardcore/pstack★ 4same name
- fullerzz/agent-skills★ 2same name
- Greg-Klein/implementation-factory★ 2same name
- Greg-Klein/implementation-harness★ 2same name
- jonmumm/skills★ 2same name
- krimvp/xpl★ 2same name
- Wanghaoyihaoyi/agent-skills★ 2same name
12 more not listed
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.
Used alongsideProjects with it also use poteto-help, principle-explain-the-number and 9 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.
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 9 projects that use this
juancamiloqhzSkillprinciple-explain-the-number
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Also in 18 projects that use this
Xia-AtaraxiaSkillmake-bot-ui
Builds a small web page whose buttons wake an agent over a webhook: a local server keeps the sender key server-side and POSTs JSON to a webhook-triggered routine, and the page is exposed on the existing Tailscale node. Use for \"make a bot UI\", \"a dashboard with buttons that trigger the agent\", \"wake the bot from a page\", handing a webhook sender key to the server without pasting it in chat, or putting that UI on the tailnet. Not for general frontend work - use principle-frontend; not for tailnet health or reachability - use tailscale.
Also in 17 projects that use this
jtarorehSkillpoteto-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 5 projects that use this
Xia-AtaraxiaSkillbenchmark-checklist
Vets performance measurements for the limiter, tuning, physical limits, errors, repeatability, relevance, and proof that timed work happened. It applies to 'check this benchmark', 'report this speedup', measured regressions, and choosing a library or configuration from numbers. It reports spread and gaps before drawing a conclusion. Not for general testing policy or choosing test oracles - use principle-testing.
Also in 18 projects that use this
alexnthnzSkillin-your-own-words
Restate in your own words what you think the user's goals are and what problem they're trying to solve. Use for /keel:in-your-own-words.
Also in 8 projects that use this
In this repository39 other files it gives its agents.
- architectSkill
- arenaSkill
- automate-meSkill
- blast-radiusSkill
- create-verification-skillSkill
- figure-it-outSkill
- interrogateSkill
- maintain-verification-skillSkill
- poteto-modeSkill
- principle-boundary-disciplineSkill
- principle-build-the-leverSkill
- principle-encode-lessons-in-structureSkill
- principle-exhaust-the-design-spaceSkill
- principle-experience-firstSkill
- principle-fix-root-causesSkill
- principle-foundational-thinkingSkill
- principle-guard-the-context-windowSkill
- principle-laziness-protocolSkill
- principle-make-operations-idempotentSkill
- principle-migrate-callers-then-delete-legacy-apisSkill
- principle-minimize-reader-loadSkill
- principle-model-the-domainSkill
- principle-never-block-on-the-humanSkill
- principle-outcome-oriented-executionSkill
- principle-prove-it-worksSkill
- principle-redesign-from-first-principlesSkill
- principle-separate-before-serializing-shared-stateSkill
- principle-sequence-verifiable-unitsSkill
- principle-subtract-before-you-addSkill
- principle-type-system-disciplineSkill
- recallSkill
- reflectSkill
- setup-pstackSkill
- show-me-your-workSkill
- tddSkill
- teachSkill
- typescript-best-practicesSkill
- unslopSkill
- whySkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
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.

