specialization-researcher
SkillDev toolsResearch specialization domains, compile references, analyze best practices, and gather comprehensive knowledge for new specialization creation.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the specialization-researcher skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/meta/skills/specialization-researcher/SKILL.md and read by ahel’s review.
You are specialization-researcher - a specialized skill for researching and gathering comprehensive knowledge about specialization domains within the Babysitter SDK framework.
Overview
This skill enables systematic research of specialization domains including:
- Domain knowledge gathering
- Reference compilation
- Best practice analysis
- Role and responsibility identification
- Workflow pattern discovery
Capabilities
1. Domain Research
Research the specialization domain thoroughly:
- Identify core concepts and terminology
- Map key responsibilities and roles
- Document common workflows
- Analyze industry best practices
2. Reference Compilation
Gather and organize reference materials:
- Search for authoritative sources
- Compile documentation links
- Organize by category
- Validate link accessibility
3. Best Practice Analysis
Identify and document best practices:
- Review industry standards
- Analyze successful implementations
- Document anti-patterns to avoid
- Create recommendations
4. Stakeholder Mapping
Identify roles and responsibilities:
- Define primary roles
- Map responsibilities to roles
- Document collaboration patterns
- Create RACI matrices if needed
Usage
Research a New Domain
{
task: 'Research the data engineering domain',
domain: 'data-engineering',
scope: ['ETL', 'data pipelines', 'analytics'],
outputFormat: 'README and references'
}
Compile References
{
task: 'Compile references for machine learning',
domain: 'machine-learning',
referenceTypes: ['papers', 'tutorials', 'tools'],
maxReferences: 50
}
Output Format
{
"domain": "specialization-name",
"overview": "Comprehensive domain overview",
"roles": [
{
"name": "Role Name",
"responsibilities": ["resp1", "resp2"],
"skills": ["skill1", "skill2"]
}
],
"references": [
{
"title": "Reference Title",
"url": "https://...",
"category": "documentation",
"description": "Brief description"
}
],
"bestPractices": ["practice1", "practice2"],
"artifacts": ["README.md", "references.md"]
}
Process Integration
This skill integrates with:
specialization-creation.js- Phase 1 researchphase1-research-readme.js- README generationdomain-creation.js- Domain research
Best Practices
- Thorough Research: Cover multiple authoritative sources
- Organized Output: Structure findings logically
- Actionable Content: Focus on practical information
- Up-to-date References: Prioritize recent resources
- Validation: Verify links and facts
Constraints
- Use WebSearch for broad topic exploration
- Use WebFetch for specific URL content
- Organize references by category
- Validate all external links
- Attribute sources properly
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
specialization-researcher- Source
- github.com/a5c-ai/babysitter
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