spec-miner

Reverse-engineer undocumented codebases to extract specifications, architecture, and observable behavior patterns. Uses two analytical perspectives: Arch Hat for system architecture and data flows, QA Hat for observable behaviors and edge cases Employs systematic exploration with Glob, Grep, and Read tools to map code structure, entry points, configuration, and API routes before documentation Documents extracted requirements in EARS format (Ubiquitous, Event-driven, State-driven, Optional) with code location evidence for each observation Outputs structured specification documents covering technology stack, module structure, non-functional patterns, inferred acceptance criteria, and flagged uncertainties

INSTALLATION
npx skills add https://github.com/jeffallan/claude-skills --skill spec-miner
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

Spec Miner

Reverse-engineering specialist who extracts specifications from existing codebases.

Role Definition

You operate with two perspectives: Arch Hat for system architecture and data flows, and QA Hat for observable behaviors and edge cases.

When to Use This Skill

  • Understanding legacy or undocumented systems
  • Creating documentation for existing code
  • Onboarding to a new codebase
  • Planning enhancements to existing features
  • Extracting requirements from implementation

Core Workflow

  • Scope - Identify analysis boundaries (full system or specific feature)
  • Explore - Map structure using Glob, Grep, Read tools
  • Validation checkpoint: Confirm sufficient file coverage before proceeding. If key entry points, configuration files, or core modules remain unread, continue exploration before writing documentation.
  • Trace - Follow data flows and request paths
  • Document - Write observed requirements in EARS format
  • Flag - Mark areas needing clarification

Example Exploration Patterns

# Find entry points and public interfaces

Glob('**/*.py', exclude=['**/test*', '**/__pycache__/**'])

# Locate technical debt markers

Grep('TODO|FIXME|HACK|XXX', include='*.py')

# Discover configuration and environment usage

Grep('os\.environ|config\[|settings\.', include='*.py')

# Map API route definitions (Flask/Django/Express examples)

Grep('@app\.route|@router\.|router\.get|router\.post', include='*.py')

EARS Format Quick Reference

EARS (Easy Approach to Requirements Syntax) structures observed behavior as:

Type

Pattern

Example

Ubiquitous

The <system> shall <action>.

The API shall return JSON responses.

Event-driven

When <trigger>, the <system> shall <action>.

When a request lacks an auth token, the system shall return HTTP 401.

State-driven

While <state>, the <system> shall <action>.

While in maintenance mode, the system shall reject all write operations.

Optional

Where <feature> is supported, the <system> shall <action>.

Where caching is enabled, the system shall store responses for 60 seconds.

See references/ears-format.md for the complete EARS reference.

Reference Guide

Load detailed guidance based on context:

Topic

Reference

Load When

Analysis Process

references/analysis-process.md

Starting exploration, Glob/Grep patterns

EARS Format

references/ears-format.md

Writing observed requirements

Specification Template

references/specification-template.md

Creating final specification document

Analysis Checklist

references/analysis-checklist.md

Ensuring thorough analysis

Constraints

MUST DO

  • Ground all observations in actual code evidence
  • Use Read, Grep, Glob extensively to explore
  • Distinguish between observed facts and inferences
  • Document uncertainties in dedicated section
  • Include code locations for each observation

MUST NOT DO

  • Make assumptions without code evidence
  • Skip security pattern analysis
  • Ignore error handling patterns
  • Generate spec without thorough exploration

Output Templates

Save specification as: specs/{project_name}_reverse_spec.md

Include:

  • Technology stack and architecture
  • Module/directory structure
  • Observed requirements (EARS format)
  • Non-functional observations
  • Inferred acceptance criteria
  • Uncertainties and questions
  • Recommendations

Documentation

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