菜单
Create high-quality ToolUniverse skills following test-driven, implementation-agnostic methodology.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/mims-harvard/ToolUniverse --skill create-tooluniverse-skill命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory work.
Gene-set enrichment analysis — GO (Biological Process, Molecular Function, Cellular Component), KEGG, Reactome pathway enrichment via clusterProfiler, gseapy, ORA, GSEA. Use for interpreting DEG lists, screen hit lists, or any gene-list-to-pathways query. Includes simplify-cutoff handling and union-vs-total denominator conventions for percent-DE questions.
Comprehensive disease characterization across genomics, transcriptomics, proteomics, and pathways for systems-level understanding. Identifies therapeutic opportunities and biomarker candidates by integrating multi-layer molecular data. Use for full-omics disease deep-dive reports, mechanism mapping, and biomarker-and-target identification from multi-omics data.
正在显示 SKILL.md
基于 SOC 职业分类
| name | create-tooluniverse-skill |
| description | Create high-quality ToolUniverse skills following test-driven, implementation-agnostic methodology. |
| disable-model-invocation | true |
Systematic workflow for creating production-ready ToolUniverse skills.
Build on the 10 pillars from devtu-optimize-skills:
operation parameterSee OPTIMIZE_INTEGRATION.md for detailed application of each pillar.
| 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).
skills/ for patternsSearch 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.
Invoke devtu-create-tool when required functionality is missing and analysis is blocked. Use devtu-fix-tool if new tools fail tests.
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 handlingUse templates from CODE_TEMPLATES.md.
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.
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.
Create summary document using PACKAGING_TEMPLATE.md. Update session tracking if creating multiple skills.
| 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 |
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.
| 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 |