mims-harvard/create-tooluniverse-skill
skills/create-tooluniverse-skill/SKILL.md
Create high-quality ToolUniverse skills following test-driven, implementation-agnostic methodology.
$ install --global
skillsauthnpx skillsauth add mims-harvard/tooluniverse create-tooluniverse-skillInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- create-tooluniverse-skill
- description:
- Create high-quality ToolUniverse skills following test-driven, implementation-agnostic methodology.
- disable-model-invocation:
- true
Create ToolUniverse Skill
Systematic workflow for creating production-ready ToolUniverse skills.
Core Principles
Build on the 10 pillars from devtu-optimize-skills:
- TEST FIRST - never document untested tools
- Verify tool contracts - don't trust function names
- Handle SOAP tools - add
operationparameter - Implementation-agnostic docs - no Python/MCP code in SKILL.md
- Foundation first - query aggregators before specialized tools
- Disambiguate carefully - resolve IDs properly
- Implement fallbacks - Primary -> Fallback -> Default
- Grade evidence - T1-T4 tiers on claims
- Quantified completeness - numeric minimums per section
- Synthesize - models and hypotheses, not just lists
See OPTIMIZE_INTEGRATION.md for detailed application of each pillar.
7-Phase Workflow
| Phase | Duration | Description | |-------|----------|-------------| | 1. Domain Analysis | 15 min | Understand use cases, data types, analysis phases | | 2. Tool Discovery | 30-45 min | Search, read configs, test tools (MANDATORY) | | 3. Tool Creation | 0-60 min | Create missing tools via devtu-create-tool | | 4. Implementation | 30-45 min | Write python_implementation.py with tested tools | | 5. Documentation | 30-45 min | Write SKILL.md (agnostic) + QUICK_START.md | | 6. Validation | 15-30 min | Run test suite, validate checklist, manual verify | | 7. Packaging | 15 min | Create summary, update tracking |
Total: ~1.5-2 hours (without tool creation).
Phase 1: Domain Analysis
- Gather concrete use cases and expected outputs
- Identify inputs, outputs, and intermediate data types
- Break workflow into logical phases
- Review existing skills in
skills/for patterns
Phase 2: Tool Discovery and Testing
Search tools in /src/tooluniverse/data/*.json (186 tool files). For each tool, read its config to understand parameters and return schema. See PARAMETER_VERIFICATION.md for common pitfalls.
Create and run a test script using test_tools_template.py. For each tool: call with known-good params, verify response format, document corrections. See TESTING_GUIDE.md for the full test suite template and procedures.
Phase 3: Tool Creation (If Needed)
Invoke devtu-create-tool when required functionality is missing and analysis is blocked. Use devtu-fix-tool if new tools fail tests.
Phase 4: Implementation
Create skills/tooluniverse-[domain]/ with:
python_implementation.py- use only tested tools, try/except per phase, progressive report writingtest_skill.py- test each input type, combined inputs, error handling
Use templates from CODE_TEMPLATES.md.
Phase 5: Documentation
Write implementation-agnostic SKILL.md using SKILL_TEMPLATE.md. Write multi-implementation QUICK_START.md using QUICKSTART_TEMPLATE.md. Key rules: zero Python/MCP code in SKILL.md, equal treatment of both interfaces in QUICK_START.
See IMPLEMENTATION_AGNOSTIC.md for format guidelines with examples.
Phase 6: Validation
Run the comprehensive test suite (see TESTING_GUIDE.md). Validate against VALIDATION_CHECKLIST.md. Perform manual verification: load ToolUniverse fresh, copy-paste QUICK_START example, verify output works.
Phase 7: Packaging
Create summary document using PACKAGING_TEMPLATE.md. Update session tracking if creating multiple skills.
Skill Integration
| Skill | When to Use | |-------|-------------| | devtu-create-tool | Critical functionality missing | | devtu-fix-tool | Tool returns errors or unexpected format | | devtu-optimize-skills | Evidence grading, report optimization |
Quality Indicators
High quality: 100% test coverage before docs, agnostic SKILL.md, multi-implementation QUICK_START, fallback strategies, parameter corrections table, response format docs.
Red flags: Docs before testing, Python in SKILL.md, assumed parameters, no fallbacks, SOAP tools missing operation, no test script.
Reference Files
| File | Content |
|------|---------|
| SKILL_TEMPLATE.md | Template for writing SKILL.md |
| QUICKSTART_TEMPLATE.md | Template for writing QUICK_START.md |
| TESTING_GUIDE.md | Test suite template and procedures |
| VALIDATION_CHECKLIST.md | Pre-release quality checklist |
| PACKAGING_TEMPLATE.md | Summary document template |
| PARAMETER_VERIFICATION.md | Tool parameter verification guide |
| OPTIMIZE_INTEGRATION.md | devtu-optimize-skills 10-pillar integration |
| IMPLEMENTATION_AGNOSTIC.md | Implementation-agnostic format guide with examples |
| CODE_TEMPLATES.md | Python implementation and test templates |
| test_tools_template.py | Tool testing script template |
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