huang-sh/deepscience/skill-template

[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

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:

Phase 2 Results:

Tool Parameter Reference

Critical Parameter Notes (from testing):

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]