What problem does it solve?
External projects often lack structured documentation, so AI agents scanning them produce shallow, low-value understanding. This Skill turns implicit team knowledge into explicit, structured documents that AI memory engines can index and retrieve.
Core Features & Use Cases
- Documentation Assessment: Diagnoses a project's documentation state across four scenarios (structured docs, code-only, scattered docs, split repos) and recommends an appropriate path.
- Guided vs Autonomous Paths: Presents a Guided path (3-7 days of structured knowledge building) or an Autonomous path (scanning existing docs) and lets the user decide.
- Three-Layer Knowledge Injection: Produces a domain glossary, business rules table, action mapping, and reusable pattern documents with YAML frontmatter templates ready for FTS5 and vector indexing.
- Use Case: When deploying an AI agent into a client's codebase that has no docs, use this Skill to derive a documentation skeleton from code structure, then guide the team to fill in business concepts, rules, and operation mappings.
Quick Start
Ask the AI to evaluate my project's documentation status and guide me through building a structured knowledge base for it.
