how

Files (4)

• SKILL.md
• openai.yaml · agents/
• explainer-prompt.md · references/
• explorer-prompt.md · references/

SKILL.md (first lines)

# How

Before delegating, read [the harness instructions](../../harness/README.md) and the active harness file. Map agent names, tool arguments, and model roles there.

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`: the harness's general-purpose agent (`general-purpose` on Claude Code, `generalPurpose` on Cursor)
- `model`: your configured how-explorer model (harness default)
- `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 subagent that explores and explains in one pass:

- `subagent_type`: the harness's general-purpose agent
- `model`: your configured how-explainer model (harness default)
- `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 subagent to synthesize their findings into one explanation:

- `subagent_type`: the harness's general-purpose agent
- `model`: your configured how-explainer model (harness default)
- `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 alexanderop/pstack, MIT.

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