| name | pitchdocs |
| description | Generate marketing-quality repository documentation from codebase analysis. Scans 10 signal categories, extracts features with file-level evidence, and produces README, CHANGELOG, ROADMAP, and 15+ more docs. Zero runtime dependencies. For AI context file management, see ContextDocs. |
| version | 2.1.0 |
| author | Little Bear Apps |
| tags | ["documentation","readme","changelog","marketing","quality-scoring","claude-code-plugin"] |
PitchDocs — AI Documentation Plugin
Overview
PitchDocs is a pure Markdown Claude Code plugin that scans any codebase and generates professional, marketing-ready repository documentation. Every feature claim traces to an actual file path — no hallucinated marketing copy.
15 skills, 16 slash commands (14 active + 2 stubs), 4 agents (3 pipeline + 1 per-project freshness checker), 1 auto-loaded rule + 2 installable rules, 1 opt-in hook. 100% Markdown, zero runtime dependencies, MIT licensed.
When to Use
- Starting a new open-source project and need professional docs fast
- Overhauling an existing README that undersells your project
- Preparing for a public launch or Product Hunt submission
- Auditing documentation completeness across 20+ files
- Creating changelogs, roadmaps, or user guides from existing code and git history
Instructions
-
Install the plugin:
/plugin marketplace add littlebearapps/lba-plugins
/plugin install pitchdocs@lba-plugins
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Navigate to any project repository
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Run commands:
/pitchdocs:readme — Generate a marketing-quality README/pitchdocs:docs-audit — Audit documentation completeness (20+ file checklist)/pitchdocs:features — Extract features with file-level evidence/pitchdocs:changelog — Generate CHANGELOG from git history/pitchdocs:ai-context — Stub: redirects to ContextDocs/pitchdocs:llms-txt — Generate llms.txt for AI discoverability/pitchdocs:docs-verify — Quality scoring (0-100) with link checking/pitchdocs:roadmap — Generate ROADMAP from GitHub milestones/pitchdocs:user-guide — Generate task-oriented user guides/pitchdocs:launch — Generate launch and promotion content/pitchdocs:doc-refresh — Refresh all docs after version bumps/pitchdocs:platform — Detect hosting platform feature support/pitchdocs:visual-standards — Visual formatting standards for docs/pitchdocs:geo — GEO optimisation for AI citation readiness/pitchdocs:activate — Install per-project rules, agent, and hook/pitchdocs:context-guard — Stub: redirects to ContextDocs
Output Format
Each command produces Markdown files written directly to the repository. The orchestration agent follows a 4-step workflow:
- Discover — Scan codebase across 10 signal categories
- Extract — Identify features with file-level evidence, classify by tier (Hero/Core/Supporting)
- Write — Generate documentation with benefit-driven language and GEO-optimised structure
- Validate — Check quality against the 4-question test and doc standards
Examples
Feature extraction output:
Hero Feature: Evidence-based feature extraction
Evidence: .claude/skills/feature-benefits/SKILL.md
Benefit: Every feature claim traces to actual code — no hallucinated marketing copy
Category: Confidence gained
README generation produces:
- Hero section with one-liner + badges
- "Why [Project]?" with problem/solution table
- Quick start with Time to Hello World target
- Features with emoji+bold+em-dash bullets
- Comparison table vs alternatives
- Documentation links and contributing CTA
Notes
- Works with 9 AI tools: Claude Code, OpenCode, Codex CLI, Cursor, Windsurf, Cline, Gemini CLI, Aider, Goose
- Cross-platform: GitHub, GitLab, and Bitbucket
- GEO-optimised for AI citation (ChatGPT, Perplexity, Google AI Overviews)
- Content filter mitigation built in for CODE_OF_CONDUCT, LICENSE, and SECURITY files
- All knowledge stored as structured YAML+Markdown — no JavaScript, no Python, no build step
