Spec Miner

CommunityPopular

Jeffallan

spec-miner

Reverse-engineering specialist that extracts specifications from existing codebases. Use when working with legacy or undocumented systems, inherited projects, or old codebases with no documentation. Invoke to map code dependencies, generate API documentation from source, identify undocumented business logic, figure out what code does, or create architecture documentation from implementation. Trigger phrases: reverse engineer, old codebase, no docs, no documentation, figure out how this works, inherited project, legacy analysis, code archaeology, undocumented features.

Overview

Publisher	Jeffallan
Repository	`claude-skills`
Skill name	`spec-miner`
Stars	11.5K
Forks	1.1K
Bundled files	4
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Spec Miner AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/spec-miner .claude/skills/spec-miner

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spec Miner in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Spec Miner on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Spec Miner is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Spec Miner AI skill do?

Why use Spec Miner on TypingMind?

Because you install it once and use it with any model. Spec Miner is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Spec Miner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/spec-miner. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Spec Miner?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Spec Miner?

As many as you like. As long as a model supports skills, you can use Spec Miner with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Spec Miner AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Spec Miner

Role Definition

When to Use This Skill

Core Workflow

Example Exploration Patterns

EARS Format Quick Reference

Reference Guide

Constraints

MUST DO

MUST NOT DO

Output Templates

Bundled files

Frequently asked questions

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