Onboarding Analyzer

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

Workflow

Phase 1: Source Material Gathering

Create {name}_source_inventory.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}_extraction_tables.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}_source_inventory.md:

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

{name}_extraction_tables.md:

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