how
Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which…
Skill by deymosxdeymos
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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What's inside
- Skill 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. Use why for motivation.
- License
- MIT
- Instructions
- 52 lines in SKILL.md · view on GitHub
Files (3)
- SKILL.md
- explainer-prompt.md · references/
- explorer-prompt.md · references/
SKILL.md (first lines)
# How Explore the codebase to answer "how does X work?" questions. Produce architectural explanations at the level of a senior engineer onboarding onto a subsystem, enough to build a working mental model, not so much that it reads like annotated source code. ## Step 1. Assess Complexity If the scope is ambiguous, state your interpretation and explore. The user can redirect. - **Simple** (a single module, a small utility, a narrow question such as "how does function X work"): no explorers. One explainer explores and explains in a single pass. Go to Step 2b. - **Complex** (a subsystem spanning multiple files or services, a cross-cutting feature, a full architectural overview): spawn parallel explorers first, then hand off to the explainer. Go to Step 2a. When in doubt, take the simple path. ## Step 2a. Explore (complex questions only) Decompose the question into 2 to 4 exploration angles, each a distinct slice of the subsystem. Spawn all explorers in a single message: - `subagent_type`: `generalPurpose` - `model`: your configured how-explorer model (default `grok-4.6-fast-xhigh`) - `readonly`: `true` Each explorer gets the prompt in `references/explorer-prompt.md` with its angle filled in. Then go to Step 3. ## Step 2b. Direct Explain (simple questions) Spawn one Task subagent that explores and explains in one pass: - `subagent_type`: `generalPurpose` - `model`: your configured how-explainer model (default `claude-fable-5-1-thinking-max`) - `readonly`: `true` Build its prompt from `references/explainer-prompt.md` without the explorer-findings section. Go to Step 4. ## Step 3. Synthesize (complex questions only) Once all explorers have returned, spawn one Task subagent to synthesize their findings into one explanation: - `subagent_type`: `generalPurpose` - `model`: your configured how-explainer model (default `claude-fable-5-1-thinking-max`) - `readonly`: `true` Build its prompt from `references/explainer-prompt.md` with every explorer's findings filled in. ## Step 4. Present Present the explainer's output to the user. Light edits for clarity or context from the conversation are fine. Do not substantially rewrite it. ## Output Format The explanation uses the sections defined in `references/explainer-prompt.md`, dropping any that do not apply: Overview, Key Concepts, How It Works, Where Things Live, Gotchas.
From deymosxdeymos/pstack-opencode, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 8, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/deymosxdeymos/pstack-opencode
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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- 0.496score
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Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how…
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poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work.
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Cite this page
how skill. Agent Mart. https://agentmart.dev/skills/deymosxdeymos-how (last updated 2026-10-24)