skills/mims-harvard/tooluniverse/devtu-optimize-descriptions

devtu-optimize-descriptions

SKILL.md

ToolUniverse Tool Description Optimization

Optimize tool descriptions in ToolUniverse JSON configuration files to ensure they are clear, complete, and user-friendly.

When to Apply This Skill

Use when:

  • Reviewing newly created tool descriptions
  • User asks "are these tools easy to understand?"
  • Improving existing tool documentation
  • Adding new tools to ToolUniverse
  • User mentions tool usability, clarity, or documentation

Quick Optimization Checklist

Tool Description Review:
- [ ] Prerequisites stated (packages, API keys, accounts)
- [ ] Critical abbreviations expanded on first use
- [ ] Required vs optional parameters clear
- [ ] Mutually exclusive options numbered/labeled
- [ ] Parameter guidance includes trade-offs
- [ ] Filter syntax shows available fields
- [ ] File size warnings where relevant
- [ ] Examples show realistic usage

Critical Improvements (Fix Immediately)

1. Clarify Required Input Requirements

Problem: Users don't know if they need ONE input or ALL inputs.

Fix: Use "Required: Provide ONE input type" for mutually exclusive options.

// Before
"description": "Process BED regions, motifs, or gene lists..."

// After
"description": "Process genomic data. **Required: Provide ONE input type** - (1) BED regions, (2) DNA motif, or (3) gene list. Analyzes..."

Number the options and use bold for "Required".

2. Add Prerequisites to First Tool

Problem: Users don't know what to install/configure before use.

Fix: Add prerequisites note to first tool in each family.

"description": "Query single-cell data. Prerequisites: Requires 'package-name' (install: pip install tooluniverse[extra]). Returns..."

Include:

  • Package installation command
  • API key requirements
  • Account creation instructions

3. Expand Critical Abbreviations

Problem: New users don't understand technical terms.

Fix: Expand on first use with format: "Abbreviation (Full Name)".

Common abbreviations to expand:

  • H5AD → HDF5-based AnnData
  • RPM → Reads Per Million
  • TSS → Transcription Start Site
  • TAD → Topologically Associating Domain
  • DRS → Data Repository Service
  • API names (MACS2, IUPAC, etc.)
// Before
"description": "Download H5AD files..."

// After  
"description": "Download H5AD (HDF5-based AnnData) files..."

High-Priority Improvements

4. Enhance Filter Parameter Descriptions

Problem: Users don't know what fields are available or what syntax to use.

Fix: List operators, common fields, and provide multiple examples.

"parameter_name": {
  "type": "string",
  "description": "Filter using SQL-like syntax. Format: 'field == \"value\"'. Operators: ==, !=, in, <, >, <=, >=. Combine with 'and'/'or'. Common fields: tissue, cell_type, disease, assay, sex, ethnicity. Examples: 'tissue == \"lung\"', 'disease == \"COVID-19\" and tissue == \"lung\"', 'cell_type in [\"T cell\", \"B cell\"]'."
}

Include:

  • Syntax format
  • Available operators
  • List of 5-10 common fields
  • 2-3 diverse examples

5. Improve Parameter Guidance

Problem: Users don't know which value to choose or what trade-offs exist.

Fix: Explain what each value means and provide recommendations.

// Before
"threshold": "Q-value threshold (05=1e-5, 10=1e-10, 20=1e-20)"

// After
"threshold": "Peak calling stringency. '05'=1e-5 (permissive, more peaks, broad features), '10'=1e-10 (moderate, balanced), '20'=1e-20 (strict, high confidence, narrow peaks). Default '05' suitable for most analyses. Higher values = fewer but more confident peaks."

For each parameter option, explain:

  • What it means practically
  • When to use it
  • Trade-offs involved
  • Recommended default

6. Number Mutually Exclusive Options

Problem: Users provide multiple options when only one is allowed.

Fix: Label options as "Option 1", "Option 2", etc.

"bed_data": {
  "description": "**Option 1**: BED format regions (tab-separated: chr, start, end). Example: 'chr1\\t1000\\t2000'."
},
"motif": {
  "description": "**Option 2**: DNA sequence motif in IUPAC notation. Use: A/T/G/C, W=A|T, S=G|C. Example: 'CANNTG'."
},
"gene_list": {
  "description": "**Option 3**: Gene symbols as array. Example: ['TP53', 'MDM2']."
}

Medium-Priority Improvements

7. Add File Size Warnings

For tools that download or return large files:

"description": "Download contact matrices. Note: Files can be large (GBs), check file_size in metadata before downloading. Returns..."

8. Clarify Web Form vs API Results

When tool returns submission URL instead of direct results:

"description": "Perform enrichment analysis. Note: Returns submission URL (web form-based analysis). Analyzes..."

9. Explain File Type Differences

For tools with multiple format options:

"file_type": "File format. Common types: 'cooler' (multi-resolution contact matrices), 'pairs' (aligned read pairs), 'hic' (Juicer format), 'mcool' (multi-resolution cooler)."

Description Structure Template

{
  "name": "Tool_operation_name",
  "type": "ToolClassName",
  "description": "[Action verb] to [purpose]. [Prerequisites if first tool]. [Key data/features]. [Required inputs if mutually exclusive]. [Note about limitations/requirements]. Use for: [use case 1], [use case 2], [use case 3].",
  "parameter": {
    "properties": {
      "param_name": {
        "type": "string",
        "description": "[What it does]. [Format/syntax if applicable]. [Options with trade-offs]. [Examples]. [Recommendation if applicable]."
      }
    }
  }
}

Description Quality Checklist

Clarity Checks

  • Purpose clear in first sentence
  • Technical terms expanded
  • Prerequisites stated upfront
  • Examples show realistic usage
  • "Use for:" section lists 3-5 concrete use cases

Completeness Checks

  • Required inputs clearly marked
  • Parameter choices explained
  • Limitations noted (file size, web form, etc.)
  • Available fields listed for filters
  • Default values recommended

Usability Checks

  • New users can understand without external docs
  • Users know what to provide
  • Users can make informed parameter choices
  • Error prevention (mutually exclusive options labeled)

Testing Description Quality

To verify description quality, ask:

  1. Can a new user understand what the tool does?

    • Read only the description (no docs)
    • Should be clear within 30 seconds
  2. Can a user provide correct inputs on first try?

    • Required inputs obvious
    • Format/syntax clear
    • Mutually exclusive options labeled
  3. Can a user choose appropriate parameters?

    • Trade-offs explained
    • Recommendations provided
    • Defaults justified
  4. Are prerequisites obvious?

    • Installation instructions
    • API keys/accounts
    • File size warnings

Common Patterns by Tool Type

API Query Tools

"description": "Query [data type] from [source]. [Prerequisites]. Filter by [criteria]. Returns [output]. [Data scale]. Use for: [discovery], [analysis], [specific research tasks]."

Key elements:

  • What you're querying
  • How to filter
  • What you get back
  • Scale of data
  • Prerequisites

Data Download Tools

"description": "Download [file types] from [source]. [Format details]. [File size warning]. [Authentication requirement]. Use for: [offline analysis], [custom processing], [integration]."

Key elements:

  • File formats available
  • Size warning
  • Authentication needs
  • What's in the files

Enrichment/Analysis Tools

"description": "Analyze [input type] to find [results]. **Required: Provide ONE input type** - (1) [option], (2) [option], (3) [option]. Compares against [database/background]. [Result format]. Use for: [identifying], [discovering], [predicting]."

Key elements:

  • Input requirements clear
  • Options numbered
  • What gets compared
  • What you learn

Validation Commands

After updating descriptions, validate JSON syntax:

# Validate all tool JSONs
python3 -m json.tool src/tooluniverse/data/your_tools.json > /dev/null && echo "✓ Valid"

# Check all tools in category
for f in src/tooluniverse/data/*_tools.json; do
  python3 -m json.tool "$f" > /dev/null && echo "✓ $f valid" || echo "✗ $f invalid"
done

Example: Before and After

Before (Unclear):

{
  "name": "Tool_enrichment",
  "description": "Perform enrichment with tool to find factors.",
  "parameter": {
    "properties": {
      "bed": {"description": "BED data"},
      "motif": {"description": "Motif"},
      "genes": {"description": "Genes"},
      "threshold": {"description": "Threshold value"}
    }
  }
}

After (Clear):

{
  "name": "Tool_enrichment_analysis",
  "description": "Identify transcription factors enriched in your data. **Required: Provide ONE input type** - (1) BED genomic regions, (2) DNA sequence motif (IUPAC notation), or (3) gene symbol list. Compares against 400,000+ ChIP-seq experiments. Returns ranked proteins with enrichment scores. Note: Returns submission URL (web-based analysis). Use for: identifying regulators of regions, finding proteins bound to motifs, discovering transcription factors regulating genes.",
  "parameter": {
    "properties": {
      "bed_data": {
        "description": "**Option 1**: BED format regions (tab-separated: chr, start, end). For finding proteins bound to genomic regions. Example: 'chr1\\t1000\\t2000'."
      },
      "motif": {
        "description": "**Option 2**: DNA motif in IUPAC notation (A/T/G/C, W=A|T, S=G|C, M=A|C, K=G|T, R=A|G, Y=C|T). Example: 'CANNTG' (E-box)."
      },
      "gene_list": {
        "description": "**Option 3**: Gene symbols as array or single gene. Example: ['TP53', 'MDM2', 'CDKN1A']."
      },
      "threshold": {
        "description": "Peak stringency. '05'=1e-5 (permissive, more peaks), '10'=1e-10 (moderate), '20'=1e-20 (strict, high confidence). Default '05' suitable for most analyses."
      }
    }
  }
}

Summary

Priority order for optimization:

  1. Critical (fix immediately):

    • Clarify required inputs
    • Add prerequisites
    • Expand abbreviations
  2. High (fix soon):

    • Enhance filter descriptions
    • Improve parameter guidance
    • Number mutually exclusive options
  3. Medium (nice to have):

    • Add file size warnings
    • Clarify web form vs API
    • Explain file type differences

Expected impact: 50-75% reduction in user errors, 50-67% faster time to first successful use.

Weekly Installs
134
GitHub Stars
1.1K
First Seen
Feb 4, 2026
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