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Skill mjmorales/claude-prove/skills/docs

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.From its SKILL.md

Install
npx -y skills add mjmorales/claude-prove --skill docs

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

8.4 KB, as published. Nobody here has run it

docs

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

SubcommandPurpose
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 generateFull 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.


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):

SubjectIndicatorsKey Sections
ProjectRoot dir, package.json, multiple componentsQuick start, usage, architecture, config
APIHTTP handlers, REST/GraphQL endpointsEndpoints, request/response, errors, examples
ModulePackage exports, public interfacesInstall, API surface, examples
ScriptExecutable file, CLI flagsUsage, flags table, examples
WorkflowMulti-step process, multiple toolsPrerequisites, steps, troubleshooting

AskUserQuestion header "Audience" if ambiguous:

AudienceToneDepthAssumes
ContributorCasual, directDeep on internalsTech stack familiarity
ConsumerPrecise, professionalInterface-level onlyNo internal knowledge
OperatorPractical, task-orientedConfig and operationsInfra/deployment experience
End userFriendly, no jargonSurface-levelMinimal 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".


Subcommand: agent

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

Subject Identification

AskUserQuestion header "Subject" if ambiguous:

SubjectIndicatorsRequired Contracts
Agent.md in agents dir, tools: frontmatterTriggers, input contract, output contract, workflow steps (numbered), tool permissions
APIHTTP handlers, REST/GraphQL endpointsRequest schema (params, body, headers), response schema (success + error), validation rules, error codes
ModulePackage exports, public interfacesPublic interface (exports only), parameter types/constraints, return types, side effects (I/O, state)
CodeFunctions, classes, complex logicTypes, 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

InputResolution
No argumentSession context: files created, modified, or discussed in the current session
Topic nameGrep/Glob for matching files/packages/modules
Directory pathAll 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 TypeIndicatorsHuman DocsAgent Docs
Agent (agents/*.md)tools:/model: frontmatterNoYes
Skill (skills/*/SKILL.md)name: frontmatter, workflowYesYes
Command (commands/*.md)description: frontmatterYesNo
Script (scripts/*.sh)Executable, CLI flagsYesOnly if agents invoke it
Package/Module (src/, lib/)Exports, public APIYesYes
Config (.json, .yaml)Schema, optionsYesOnly 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".


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

CommandPurpose
claude-md scan --project-root $CWD --plugin-dir $PLUGINScanner only, JSON output
claude-md subagent-context --project-root $CWD --plugin-dir $PLUGINCompact context for subagent injection

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


Anti-Patterns

Anti-PatternInstead
Reading entire filesGrep target, read specific lines
Interleaving gathering and writingComplete all reads before delegating
Omitting audience from human promptAlways 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.mdRoute 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

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.