skill-domain-discovery

Generates domain maps and skill specs from repositories and expert input.

6|1|Updated Jan 20, 2026

Search Tags:#automation #ai-agent #domain-discovery #documentation-analysis #skill-tree #domain-map #maintainer-interview

Ready to run

npx skills add https://github.com/LadyBluenotes/agent-infra --skill skill-domain-discovery

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-domain-discovery
Source: https://github.com/LadyBluenotes/agent-infra/tree/main/meta/domain-discovery
Command: npx skills add https://github.com/LadyBluenotes/agent-infra --skill skill-domain-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze library documentation and source code, then interview maintainers to discover capability domains and task-focused skills for AI coding agents. Activate when creating skills for a new library, organizing existing documentation into skill categories, or when a maintainer wants help deciding how to structure their library's agent-facing knowledge.

Core Features & Use Cases

Domain identification: extract implicit capability areas from docs and code.
Skill taxonomy: cluster tasks into domain-aligned skills and produce a domain_map.yaml and skill_spec.md.
Maintainer interviews: guide interviews to elicit developer tasks and journeys; synthesize them into structured outputs for tooling.

Quick Start

Run the domain discovery workflow on your library to generate domain_map.yaml and skill_spec.md.

Frequently Asked Questions about skill-domain-discovery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I map library documentation to actionable AI coding skills?▼

To map library documentation to actionable AI coding skills, you can analyze docs and source code to extract capability domains. This process clusters developer tasks into a structured skill taxonomy, outputting a domain map and skill specification for agent-facing knowledge.

What is the best way to organize existing documentation into skill categories for an AI agent?▼

Organizing existing documentation into skill categories requires extracting implicit capability areas from your library files. By clustering these tasks into domain-aligned skills, you generate structured outputs like domain_map.yaml and skill_spec.md for downstream tooling.

How do maintainer interviews help discover developer tasks and domain maps?▼

Maintainer interviews help discover developer tasks by guiding conversations that elicit developer journeys and capability domains. The interview insights are then synthesized into structured skill specifications and domain maps for AI coding agents.

Can I use this domain discovery workflow without any external dependencies?▼

Yes, you can run the domain discovery workflow without external dependencies. It operates independently by analyzing your library documentation and source code to produce domain_map.yaml and skill_spec.md outputs for downstream tooling.

When should I not use an automated skill taxonomy for library documentation analysis?▼

You should not use automated skill taxonomy generation when your library lacks sufficient documentation or source code for analysis. The workflow relies on extracting implicit capability areas from these inputs to successfully structure agent-facing knowledge.