// 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.
Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in. Use for /architect, 'architect this', 'design this', or non-trivial work where jumping to code would lock in the wrong shape.
Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Four LLM reviewers challenge changes from independent angles.
Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.
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.
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.
| name | how |
| description | 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. |
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:
Parse what the user is asking about:
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:
When in doubt, lean simple. You can always spawn explorers if the explainer hits a wall.
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?":
The right decomposition depends on the question. Use your judgment. Narrow questions: 2 explorers is fine. Broad subsystems: up to 4.
Spawn all explorers in a single message:
subagent_type: generalPurposemodel: composer-2.5-fastreadonly: trueEach explorer gets the same base prompt from references/explorer-prompt.md plus a specific exploration angle naming its slice. Each explorer should:
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.
Spawn a single Task subagent that explores and explains in one pass:
subagent_type: generalPurposemodel: claude-opus-4-8-thinking-xhighreadonly: trueThe 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.
Once all explorers return, spawn a single Task subagent to synthesize their findings into one coherent explanation:
subagent_type: generalPurposemodel: claude-opus-4-8-thinking-xhighreadonly: trueThe 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.
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.
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.
Triggered when the user asks for architectural issues, problems, or improvements, not just understanding.
Run the full explain flow above (Steps 1-4). You must understand the architecture before critiquing it.
After the explanation is complete, spawn architectural critics. Launch all in a single message:
| Subagent | Model |
|---|---|
| Critic A | claude-opus-4-8-thinking-xhigh |
| Critic B | gpt-5.3-codex-high-fast |
| Critic C | gpt-5.5-high-fast |
For each critic:
subagent_type: generalPurposemodel: the model from the table. These are minimum reasoning levels. The lead should escalate any model when the architecture warrants deeper analysis.readonly: trueRead references/critic-prompt.md for the prompt template. Each critic gets:
references/critique-rubric.mdSame framework as the interrogate skill. You're a pragmatic lead, not an aggregator.
Categorize findings:
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.