tooluniverse-[domain-name]
Use when [specific triggering conditions and symptoms].
- License 许可
- MIT
- 最近更新
- 2026-11-02
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- tooluniverse-[domain-name]
- description
- Use when [specific triggering conditions and symptoms].
02 资源文件 3
- 脚本python_implementation.py5.5 KB
- 参考文档QUICK_START.md7.5 KB
- 脚本test_skill.py6.6 KB
03 SKILL.md 正文
[Domain Name] Analysis
[One paragraph overview describing what this skill does, what problems it solves, and what outputs it provides.]
When to Use This Skill
Triggers:
- "[Trigger phrase 1]"
- "[Trigger phrase 2]"
- "[Trigger phrase 3]"
Use Cases:
- [Use Case 1]: [Description]
- [Use Case 2]: [Description]
- [Use Case 3]: [Description]
Core Databases Integrated
| Database | Coverage | Strengths |
|---|---|---|
| Database 1 | [What it covers] | [What it's best for] |
| Database 2 | [What it covers] | [What it's best for] |
| Database 3 | [What it covers] | [What it's best for] |
Workflow Overview
Input → Phase 1: [Name] → Phase 2: [Name] → Phase 3: [Name] → Report
Phase 1: [Phase Name]
When: [When this phase runs - e.g., "When input_param_1 provided"]
Objective: [What this phase achieves]
Tools Used
TOOL_NAME_1:
- Input:
parameter1(type, required/optional): Descriptionparameter2(type, required/optional): Description
- Output: Description of what the tool returns
- Use: What this tool provides for the analysis
TOOL_NAME_2 (Fallback):
- Input: [Parameters]
- Output: [Description]
- Use: [Purpose]
Workflow
- Query TOOL_NAME_1 with [input description]
- Extract [specific data fields] from response
- If no results → try TOOL_NAME_2 (fallback)
- Process data and add to report
- Continue with available data
Decision Logic
- Successful query: Process and display top 10-15 results
- Empty results: Note "[Database] returned no results"
- API error: Fall back to TOOL_NAME_2
- Both fail: Document unavailability and continue
Phase 2: [Phase Name]
When: [Conditions]
Objective: [Goal]
Tools Used
[Similar structure to Phase 1]
Workflow
[Step-by-step process]
Decision Logic
[How to handle different scenarios]
Phase 3: [Phase Name]
[Similar structure]
Phase 4: [Summary/Context Phase]
When: Always included
Objective: Provide context even when specific phases empty
[Structure similar to above phases]
Output Structure
Report Format
Progressive Markdown Report:
- Create report file first
- Add sections progressively
- Each section self-contained
- Handles empty data gracefully
Required Sections:
- Header: Analysis parameters and metadata
- Phase 1 Results: [Description]
- Phase 2 Results: [Description]
- Phase 3 Results: [Description]
- Phase 4 Results: [Description]
Per-Database Subsections:
- Database name and result count
- Table of results with key metadata
- Note if database returns no results
- Links or IDs for follow-up
Data Tables
Phase 1 Results: | Column 1 | Column 2 | Column 3 | | ... | ... | ... |
Phase 2 Results: | Column 1 | Column 2 | Column 3 | | ... | ... | ... |
Tool Parameter Reference
Critical Parameter Notes (from testing):
| Tool | Parameter | CORRECT Name | Common Mistake |
|---|---|---|---|
| TOOL_NAME_1 | param |
✅ actual_param_name |
❌ assumed_param_name |
| TOOL_NAME_2 | param |
✅ correct_name |
❌ function_name_param |
Response Format Notes:
- TOOL_NAME_1: Returns standard
{status: "success", data: [...]}format - TOOL_NAME_2: Returns list directly (not wrapped in status/data)
- TOOL_NAME_3: Returns dict with custom structure
{field1: ..., field2: ...}
SOAP Tools (if applicable):
- TOOL_NAME_4: Requires
operationparameter (e.g.,operation="method_name") - See QUICK_START.md for side-by-side Python/MCP examples
Fallback Strategies
Phase 1: [Phase Name]
- Primary: TOOL_NAME_1 ([reason it's primary])
- Fallback: TOOL_NAME_2 ([what it provides instead])
- Default: Continue with noting data unavailable
Phase 2: [Phase Name]
- Primary: TOOL_NAME_3
- Fallback: [Alternative approach]
- Default: [How to proceed]
Common Use Patterns
Pattern 1: [Use Case Name]
Input: [Description of typical input]
Workflow: Phase 1 → Phase 3 → Report
Output: [What user gets]
Pattern 2: [Use Case Name]
Input: [Description]
Workflow: [Which phases run]
Output: [Result type]
Pattern 3: [Comprehensive Analysis]
Input: [Multiple inputs]
Workflow: All phases
Output: [Complete analysis]
Quality Checks
Data Completeness
- [ ] At least one phase completed successfully
- [ ] Each database result includes source attribution
- [ ] Empty results explicitly noted (not silently omitted)
- [ ] All required fields documented in tables
- [ ] IDs provided for follow-up analysis
Biological/Scientific Validity
- [ ] Results consistent with known [domain] knowledge
- [ ] Cross-database results show expected overlaps
- [ ] Anomalies flagged for review
- [ ] Data quality indicators included
Report Quality
- [ ] All sections present even if "no data"
- [ ] Tables formatted consistently
- [ ] Source databases clearly attributed
- [ ] Follow-up recommendations if data sparse
Limitations & Known Issues
Database-Specific
- Database 1: [Known limitations, coverage gaps, update frequency]
- Database 2: [Limitations]
- Database 3: [Limitations]
Technical
- Response formats: Different tools use different structures (handled in implementation)
- Rate limits: [Any rate limiting concerns]
- Version differences: [Database version considerations]
Analysis
- [Domain]-specific limitation 1: [Description]
- [Domain]-specific limitation 2: [Description]
Summary
[Domain] Analysis Skill provides:
- ✅ [Capability 1 with database]
- ✅ [Capability 2 with databases]
- ✅ [Capability 3 with databases]
- ✅ [Capability 4]
Outputs: Markdown report with [description of content]
Best for: [Primary use cases and target users]
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