superagent: Skill for Claude Code

Codebase Scanner

You are a technical analyst. Your job is to scan the project codebase and produce accurate, project-specific documentation used by all downstream agents.

Step 1: Check Optional Plugin Dependencies

Check whether the two optional enhancement plugins are available:

understand-anything  →  /plugin list | grep understand-anything
context-mode         →  /plugin list | grep context-mode

These plugins are optional. They improve scan quality but are not required:

• understand-anything (Lum1104/Understand-Anything) — provides deeper semantic code analysis
• context-mode (mksglu/context-mode) — routes large outputs through a sandbox to protect the context window

If both are present, use them in Steps 3–4 as described below. If either or both are missing, proceed with the native fallback approach: use find, grep, cat, and git commands directly, routing large outputs through ctx_execute / ctx_execute_file if context-mode is available, otherwise summarise inline.

Note: To install the optional plugins manually:

/plugin marketplace add Lum1104/Understand-Anything && /plugin install understand-anything
/plugin marketplace add mksglu/context-mode && /plugin install context-mode@context-mode

Step 2: Determine Scan Mode

Check if .claude/pipeline/project-doc.md exists.

• Does not exist → FULL SCAN (first run)
• Exists → DELTA SCAN

Step 3A: Full Scan

Use understand-anything to analyse the entire codebase. If context-mode is available (verified in Step 1), route ALL output through its tools (ctx_batch_execute / ctx_execute_file) — never dump raw file contents into the main context window. If context-mode is not available, summarise each file's findings inline and avoid printing raw file contents.

Produce .claude/pipeline/project-doc.md using the following structure (based on the architecture-blueprint-generator pattern):

# Project Documentation
> Generated: [timestamp] | Mode: FULL

## Tech Stack
- Runtime: [e.g. Node.js 20, Python 3.11]
- Language: [e.g. TypeScript, Python]
- Framework: [e.g. Next.js 14 App Router, FastAPI]
- Database: [e.g. PostgreSQL via Prisma]
- Styling: [e.g. Tailwind CSS]
- State Management: [e.g. Zustand, Redux]

## Dependencies
[Key libraries with versions, grouped by: core / dev / testing]

## Architecture Pattern
[e.g. Feature-based, Layered MVC, Clean Architecture]
[Describe how the project is structured and why]

## Folder Structure
[Top-level directory map with purpose of each folder]

## Code Style Conventions
[Naming patterns, file naming, import ordering, export patterns]
[Inferred from actual code — not guessed]

## Modularity Practices
[How concerns are separated, shared module locations, service patterns]

## Data Architecture
[Entity relationships, data access patterns, ORM usage]

## Cross-Cutting Concerns
[Auth/authz approach, error handling patterns, logging, validation]

## Service Communication
[REST / GraphQL / event-driven — document what actually exists]

## Test Coverage
- Overall coverage: [X%]
- Testing framework: [e.g. Jest, Vitest, Pytest]
- Key untested areas: [list]
- Test patterns used: [unit / integration / e2e]

## Entry Points
[Main files, key config files, environment setup]

## Changed Files
[Only present in delta scans — list of files re-scanned]

## Last Scanned
[ISO timestamp]