Systematic codebase scanning for features and evidence-based feature-to-benefit translation. Extracts what a project does from its code and translates it into what users gain — generates features and benefits sections, "Why [Project]?" content, and feature audit reports. Use when writing a features table for a README…
Generative Engine Optimisation (GEO) patterns for documentation that surfaces correctly in AI-generated answers — citation capsules, crisp definitions, atomic sections, comparison tables, statistics, and semantic scaffolding. Load when optimising docs for AI citation (ChatGPT, Perplexity, Google AI Overviews, Claude).
Transforms README and CHANGELOG into platform-specific launch content — Dev.to articles, Hacker News posts, Reddit posts, Twitter/X threads, and awesome list submission PRs. Keeps promotion tethered to code artifacts, not generic marketing. Use when launching or announcing a project release.
Generates llms.txt and llms-full.txt files following the llmstxt.org specification. Provides LLM-friendly content curation for AI coding assistants (Cursor, Windsurf, Claude Code) and AI search engines. Use when generating or updating llms.txt for a repository.
Documentation guidance for projects published to npm and PyPI package registries. Covers metadata fields that affect registry pages, README cross-renderer compatibility, trusted publishing, provenance badges, and audit checks. Use when a project has package.json or pyproject.toml and is published publicly.
One-command generation and audit of the full public repository documentation set — README, CHANGELOG, ROADMAP, CONTRIBUTING, CODEOFCONDUCT, SECURITY, issue templates, PR template, and discussion templates. Use when setting up a new repo or auditing an existing one.
Platform-specific equivalents for GitLab and Bitbucket when generating repository documentation. Lookup tables for file paths, badges, Markdown rendering, CI/CD, and CLI tools. Load this skill when working on non-GitHub repos or generating cross-platform docs.
Generates READMEs with the Daytona/Banesullivan marketing framework — hero section, benefit-driven features, quickstart, comparison tables, and compelling CTAs. Produces docs that sell as well as they inform. Use when creating or overhauling a project README.
Generates ROADMAP.md from project milestones, issues, and boards (GitHub, GitLab, or Bitbucket). Structures content with mission statement, current milestone progress, upcoming milestones, and community involvement section. Use when creating or updating a project roadmap.
Generates task-oriented user guides and how-to documentation for a repository. Creates docs/guides/ with step-by-step instructions for common workflows, integrations, and advanced usage. Links guides into README.md and CONTRIBUTING.md. Use when a project needs user-facing how-to documentation beyond the README…
Visual formatting standards for repository documentation — emoji heading prefixes, horizontal rules, TOC anchors, callouts, screenshots (device dimensions, HTML patterns, captions, shadows), and image optimisation. Load when generating READMEs with visual elements or working with screenshots.
You are working on PitchDocs, a Claude Code plugin that generates marketing-quality repository documentation. This is a pure Markdown project with no code runtime.
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.