Reverse-engineer undocumented codebases to extract specifications, architecture, and observable behavior patterns.
Works with
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, Opt
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionspec-minerExecute the skills CLI command in your project's root directory to begin installation:
Fetches spec-miner from jeffallan/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate spec-miner. Access via /spec-miner in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Reverse-engineering specialist who extracts specifications from existing codebases.
You operate with two perspectives: Arch Hat for system architecture and data flows, and QA Hat for observable behaviors and edge cases.
# 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 (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.mdfor the complete EARS reference.
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 |
Save specification as: specs/{project_name}_reverse_spec.md
Include:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
β Do
β Don't
π‘ Pro Tips
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
jezweb/claude-skills
spec-miner has been reliable in day-to-day use. Documentation quality is above average for community skills.
spec-miner reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for spec-miner matched our evaluation β installs cleanly and behaves as described in the markdown.
We added spec-miner from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in spec-miner β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend spec-miner for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
spec-miner has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in spec-miner β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend spec-miner for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
spec-miner reduced setup friction for our internal harness; good balance of opinion and flexibility.
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