Rai Discover Scan

Discovery Scan

Deprecated: Use /rai-discover instead, which runs the full pipeline (detect → extract → describe → document → build) in one pass. This skill is kept for backward compatibility.

Purpose

Extract symbols from the codebase and synthesize meaningful descriptions for each component. Produces a draft component catalog ready for human validation.

Mastery Levels (ShuHaRi)

• Shu: Follow all steps, synthesize descriptions for all public symbols
• Ha: Filter to public APIs only; skip internal helpers automatically
• Ri: Custom synthesis prompts for domain-specific codebases

Context

When to use: After /rai-discover-start has created context, or for targeted scan of a specific directory.

When to skip: work/discovery/components-draft.yaml exists and is current.

Inputs: work/discovery/context.yaml from /rai-discover-start, OR explicit path argument.

Steps

Step 1: Extract Symbols

rai discover scan {root_dir} --language {language} --output json

Step 2: Run Analysis

rai discover scan {root_dir} --language {language} --output json | rai discover analyze --output human

Produces work/discovery/analysis.json with:

• Confidence scores per component (high ≥70 / medium 40-69 / low <40)
• Auto-categorization from path conventions and naming patterns
• Hierarchical folding (methods grouped under parent classes)
• Module grouping (for parallel AI synthesis batches)

Step 3: Synthesize Descriptions

Per component synthesis:

1. Purpose — What does it do? Why does it exist? (1-2 sentences, focus on reuse value)
2. Category — Verify or correct auto_category
3. Dependencies — Key types from signature (specific, not generic)

Step 4: Generate IDs & Write Draft

ID pattern: comp-{module}-{name} (lowercase, hyphens for underscores).

Write work/discovery/components-draft.yaml:

generated_at: {ISO_TIMESTAMP}
symbol_count: {N}
components:
  - id: comp-scanner-symbol
    name: Symbol
    kind: class
    file: src/raise_cli/discovery/scanner.py
    line: 44
    signature: "class Symbol(BaseModel)"
    purpose: "Represents a code symbol extracted from source files."
    category: model
    depends_on: [pydantic.BaseModel]
    internal: false
    validated: false

Step 5: Display Summary

## Discovery Scan Complete

**Scanned:** {path} | **Language:** {language} | **Symbols:** {total}
**Categories:** Models: {N}, Services: {N}, Utilities: {N}
**Output:** `work/discovery/components-draft.yaml`

**Next:** `/rai-discover-validate`

Output

Quality Checklist

• Synthesis focuses on reuse value (what/why, not how)
• Categories match symbol roles (see category table below)
• Dependencies are specific types, not generic packages
• Large codebases (>100 symbols): scan in chunks by directory
• NEVER describe implementation details in purpose ("Uses a loop to...")

References

• Previous: /rai-discover-start
• Next: /rai-discover-validate
• CLI: rai discover scan --help, rai discover analyze --help
• Categories: service, model, utility, handler, parser, builder, schema, command, test