Onboarding Analyzer

Gather source material and extract key information from a codebase for onboarding documentation.

Workflow

Phase 1: Source Material Gathering

Create {name}sourceinventory.md with the following procedure:

1.1 Identify Keywords

• Identify the most general keyword for the feature (e.g., "auth", "cache", "validation")
• Break it into related terms (e.g., "auth" → "auth", "login", "token", "session")

1.2 BM25 Search

• Uses git ls-files to search all tracked files. Pass each term with -t:

``bash uv run /path/to/skill/scripts/search.py -t auth -t login -t token `` VERY IMPORTANT: YOU MUST USE search.py using uv.

• Record top results with path and 1-2 sentence summary
• For each file found, note:

- File path - Entry points (main functions, exports) - Brief 1-line description

1.3 Identify Plans/Specs

• Search for design docs, specs, requirements:

``bash uv run /path/to/skill/scripts/search.py -t spec -t design -t plan ``

• Note if absent.

Phase 2: Key Information Extraction

Create {name}extractiontables.md with structured tables:

2.1 Function Table

2.2 Dependency Table

2.3 Data Flow

Document the "happy path":

1. Entry: main() receives request
2. Calls: validate() checks input
3. Calls: process() does work
4. Returns: result to caller

Key Questions to Answer

During gathering:

• What feature/phase is being documented?
• Which files are main implementation?
• What existing documentation exists?

During extraction:

• What are the main functions/classes?
• What calls what?
• What external APIs are used?

Success Criteria

{name}sourceinventory.md:

• Keywords and related terms listed
• Files found via BM25 search with summaries and entry points
• Plans/specs noted (or marked absent)

{name}extractiontables.md:

• Function table with accurate line numbers
• Dependency table with versions
• Data flow from entry to exit documented