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how

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.

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仓库
paperclipai/agent-plugins
最近来源活动
2026年10月10日 12:58
检测到的 SKILL.md 语言
英语
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安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

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决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

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SKILL.md
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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.
disable-model-invocation
true
# How Read [runtime](../runtime/SKILL.md) for host-specific tools and paths. 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. Each spawn below names a role line in the `models.md` rule and a default. Set `model` to that line's value, or to the default if the rule or the line is missing. Leave `model` unset when the value is `auto` or `inherit-parent`. If the host rejects a model, follow the runtime skill's model fallback rules. ## 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: - Agent: general-purpose - `model`: the `how explorer` line, default `inherit-parent` - Access: read-only 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 subagent that explores and explains in one pass: - Agent: general-purpose - `model`: the `how explainer` line, default `inherit-parent` - Access: read-only 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 subagent to synthesize their findings into one explanation: - Agent: general-purpose - `model`: the `how explainer` line, default `inherit-parent` - Access: read-only 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.
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