mims-harvard/tooluniverse/skill-template

Claude Code and agent skill by mims-harvard/tooluniverse

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[Complete description of what the skill does, which databases it uses, and when to use it. Include specific trigger phrases like "analyze [domain]", "find [data type]", etc. This description is the primary way Claude determines when to use your skill.]

Install

npx vskill@latest install mims-harvard/tooluniverse/skill-template

SKILL.md

[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:

  1. [Use Case 1]: [Description]
  2. [Use Case 2]: [Description]
  3. [Use Case 3]: [Description]

Core Databases Integrated

DatabaseCoverageStrengths
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): Description
  • parameter2 (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
  1. Query TOOL_NAME_1 with [input description]
  2. Extract [specific data fields] from response
  3. If no results → try TOOL_NAME_2 (fallback)
  4. Process data and add to report
  5. 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:

  1. Header: Analysis parameters and metadata
  2. Phase 1 Results: [Description]
  3. Phase 2 Results: [Description]
  4. Phase 3 Results: [Description]
  5. 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 1Column 2Column 3
.........

Phase 2 Results:

Column 1Column 2Column 3
.........

Tool Parameter Reference

Critical Parameter Notes (from testing):

ToolParameterCORRECT NameCommon Mistake
TOOL_NAME_1param✅ actual_param_name❌ assumed_param_name
TOOL_NAME_2param✅ 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 operation parameter (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:

  1. ✅ [Capability 1 with database]
  2. ✅ [Capability 2 with databases]
  3. ✅ [Capability 3 with databases]
  4. ✅ [Capability 4]

Outputs: Markdown report with [description of content]

Best for: [Primary use cases and target users]

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

7-day trend score
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