docs

name	docs
description	Unified documentation skill. Generates human-readable docs (READMEs, guides, API references, getting-started), LLM-optimized agent/API docs, and regenerates CLAUDE.md. Triggers: "write docs", "document this", "README", "API reference", "getting-started", "LLM docs", "agent docs", "CLAUDE.md". For single-directive CLAUDE.md growth, use `/prove:remember` instead.

docs

Dispatches by subcommand. Follows references/interaction-patterns.md for all AskUserQuestion usage.

Subcommand	Purpose
human [subject]	Human-readable docs — delegates to technical-writer agent
agent [subject]	LLM-optimized agent/API/module docs
both [subject] (default)	Auto-docs: resolve scope, run both audiences
claude-md generate	Full CLAUDE.md generation via claude-prove claude-md CLI

Parse first token of $ARGUMENTS as subcommand. If absent, default to both with empty subject (session context).

For single-directive growth of CLAUDE.md outside the prove-managed block, defer to /prove:remember <directive> — it owns optimize + certify + safe-insertion.

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Subcommand: human

Delegate to technical-writer subagent. One-pass gather, one-pass delegate.

Subject + Audience

AskUserQuestion header "Subject" if ambiguous (include "Research & proceed" with <=3 options):

Subject	Indicators	Key Sections
Project	Root dir, package.json, multiple components	Quick start, usage, architecture, config
API	HTTP handlers, REST/GraphQL endpoints	Endpoints, request/response, errors, examples
Module	Package exports, public interfaces	Install, API surface, examples
Script	Executable file, CLI flags	Usage, flags table, examples
Workflow	Multi-step process, multiple tools	Prerequisites, steps, troubleshooting

AskUserQuestion header "Audience" if ambiguous:

Audience	Tone	Depth	Assumes
Contributor	Casual, direct	Deep on internals	Tech stack familiarity
Consumer	Precise, professional	Interface-level only	No internal knowledge
Operator	Practical, task-oriented	Config and operations	Infra/deployment experience
End user	Friendly, no jargon	Surface-level	Minimal technical background

Context Gathering

• Grep to locate targets, then read specific lines
• Document public interface only — never follow imports recursively
• Complete all reads before delegating

Delegation Prompt

Invoke technical-writer agent with:

Document [SUBJECT_TYPE]: [SUBJECT_NAME]
Audience: [AUDIENCE_TYPE]

Source: [FILE_PATH]:[LINE_RANGE]

Context:
[MINIMAL RELEVANT CODE/CONFIG]

Requirements:
- Output: [project-readme | api-reference | module-docs | script-docs | workflow-guide]
- Audience: [contributor | consumer | operator | end-user]
- Include: [subject-specific sections the template does not cover by default]
- Format: Markdown, no YAML frontmatter unless docs system requires it

Validation

• Title states what the subject is
• First paragraph answers "what is this and why use it?"
• Examples are concrete and runnable (no foo/bar/...)
• Headings create a scannable outline
• Structured data uses tables, not prose
• No unexplained jargon on first use
• Tone matches target audience

AskUserQuestion header "Quality": "Approve" / "Revise".

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Subcommand: agent

Generate machine-parseable, LLM-consumable documentation. Delegate to technical-writer with agent-doc output flag.

Subject Identification

AskUserQuestion header "Subject" if ambiguous:

Subject	Indicators	Required Contracts
Agent	.md in agents dir, tools: frontmatter	Triggers, input contract, output contract, workflow steps (numbered), tool permissions
API	HTTP handlers, REST/GraphQL endpoints	Request schema (params, body, headers), response schema (success + error), validation rules, error codes
Module	Package exports, public interfaces	Public interface (exports only), parameter types/constraints, return types, side effects (I/O, state)
Code	Functions, classes, complex logic	Types, behavior, edge cases

Delegation Prompt

Document [SUBJECT_TYPE]: [SUBJECT_NAME]

Source: [FILE_PATH]:[LINE_RANGE]

Context:
[MINIMAL RELEVANT CODE/CONFIG]

Requirements:
- Output: [agent-doc | api-doc | module-doc]
- Include: [specific contracts from table above]
- Format: YAML frontmatter + structured markdown

Validation

• YAML frontmatter has name, type
• All contracts from Subject table addressed
• Examples use concrete values (no .../foo/bar)
• Error/failure conditions documented

AskUserQuestion header "Quality": "Approve" / "Revise".

---

Subcommand: both (default)

Resolve scope, classify subjects, run agent docs first (define contracts), then human docs.

Step 1 — Resolve Scope

Input	Resolution
No argument	Session context: files created, modified, or discussed in the current session
Topic name	Grep/Glob for matching files/packages/modules
Directory path	All exported/public code in that directory
File path(s)	Those specific files

Session priority: new files > significantly modified > new agents/skills/commands > scripts. Skip: test files, lock files, build artifacts, self-documenting configs.

If ambiguous: AskUserQuestion header "Scope": "This session" / "Directory" / "Specific files".

Step 2 — Classify Subjects

Subject Type	Indicators	Human Docs	Agent Docs
Agent (agents/*.md)	tools:/model: frontmatter	No	Yes
Skill (skills/*/SKILL.md)	name: frontmatter, workflow	Yes	Yes
Command (commands/*.md)	description: frontmatter	Yes	No
Script (scripts/*.sh)	Executable, CLI flags	Yes	Only if agents invoke it
Package/Module (src/, lib/)	Exports, public API	Yes	Yes
Config (.json, .yaml)	Schema, options	Yes	Only if agents read it

Step 3 — Confirm

AskUserQuestion header "Doc Types":

• "Both human & agent docs (Recommended)"
• "Human docs only"
• "Agent docs only"
• "Let me pick per subject"

If human docs selected and audience non-obvious: AskUserQuestion header "Audience": "Contributor" / "Consumer" / "Operator".

AskUserQuestion header "Output":

• "Alongside source (Recommended)"
• "Centralized docs/"
• "Let me specify"

Step 4 — Delegate

Order: agent docs first (establish contracts), human docs second (can reference them). Within each type: core modules before consumers. Dispatch to human and agent subcommand workflows above.

Step 5 — Review

Present summary table (subject, human/agent, path, file count).

AskUserQuestion header "Review": "Approve all" / "Revise" / "Discard".

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Subcommand: claude-md generate

Full CLAUDE.md regeneration. Scans codebase (tech stack, conventions, structure), reads .claude/.prove.json, composes deterministic output.

Execution

1. $PLUGIN = absolute path to this plugin's root (parent of skills/)
2. $CWD = user's cwd (target project, not plugin dir)
3. Run: claude-prove claude-md generate --project-root $CWD --plugin-dir $PLUGIN
4. Display CLI output

Related CLI Subcommands

Command	Purpose
claude-md scan --project-root $CWD --plugin-dir $PLUGIN	Scanner only, JSON output
claude-md subagent-context --project-root $CWD --plugin-dir $PLUGIN	Compact context for subagent injection

Safe to re-run — the CLI owns the file.

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Anti-Patterns

Anti-Pattern	Instead
Reading entire files	Grep target, read specific lines
Interleaving gathering and writing	Complete all reads before delegating
Omitting audience from human prompt	Always include Audience:
Verbose examples with inline commentary (agent docs)	Minimal working examples
Line-by-line code explanation (agent docs)	Document behavior and contracts
Writing raw user directive to CLAUDE.md	Route through /prove:remember (optimize + certify + safe-insert)

Committing

Delegate to commit skill. Example messages:

• docs(docs): add README for cafi tool
• docs(docs): document validation-agent interface
• docs(docs): regenerate CLAUDE.md