Automated Life Science API Discovery & Tool Creation

Discover, create, validate, and integrate life science APIs into ToolUniverse.

Four-Phase Workflow

Gap Analysis → API Discovery → Tool Creation → Validation → Integration

↓ ↓ ↓ ↓ ↓

Coverage Web Search devtu-create devtu-fix Git PR

Human approval gates after: discovery, creation, validation, and before PR.

Phase 1: Discovery & Gap Analysis

1.1 Analyze Current Coverage

Load ToolUniverse, categorize tools by domain (genomics, proteomics, drug discovery, clinical, omics, imaging, literature, pathways, systems biology). Count per category.

1.2 Identify Gap Domains

Critical Gap

<5 tools in category

Moderate Gap

5-15 tools, missing key subcategories

Emerging Gap

New technologies not represented

Common gaps: single-cell genomics, metabolomics, patient registries, microbial genomics, multi-omics integration, synthetic biology, toxicology.

1.3 Web Search for APIs

For each gap domain, run multiple queries:

"[domain] API REST JSON"

— direct API search

"[domain] public database"

— database discovery

"[domain] API 2025 OR 2026"

— recent releases

"[domain] database" site:nar.oxfordjournals.org

— NAR Database Issue

Extract: base URL, endpoints, auth method, parameter schemas, rate limits.

1.4 Score and Prioritize

Criterion

Max Points

Documentation Quality

20

API Stability

15

Authentication Simplicity

15

Coverage

15

Maintenance

10

Community

10

License

10

Rate Limits

5

High priority (>=70), Medium (50-69), Low (<50).

1.5 Generate Discovery Report

Coverage analysis, prioritized candidates with scores, implementation roadmap.

Phase 2: Tool Creation

For each API, use

Skill(skill="devtu-create-tool")

or follow these patterns.

Architecture Decision

Multiple endpoints → multi-operation tool (single class, multiple JSON wrappers)

Single endpoint → single-operation acceptable

Key Steps

Design tool class following template — see

references/tool-templates.md

Create JSON config with oneOf return_schema

Find real test examples (use List endpoint → extract IDs → verify)

Register in

default_config.py

Critical Requirements

return_schema MUST have

oneOf

(success + error schemas)

test_examples MUST use real IDs (NO placeholders)

Tool name <= 55 characters

NEVER raise exceptions in

run()

— return error dict

Set timeout on all HTTP requests (30s)

Phase 3: Validation

Full guide:

references/validation-guide.md

Quick Validation Checklist

Schema

oneOf structure, data wrapper, error field

Placeholders

No TEST/DUMMY/PLACEHOLDER in test_examples

Loading

3-step check (class registered, config registered, wrappers generated) Integration tests : python scripts/test_new_tools.py [api_name] -v → 100% pass Fix failures with Skill(skill="devtu-fix-tool") . Phase 4: Integration Use Skill(skill="devtu-github") or: Create branch: feature/add-[api-name]-tools Stage tool files + default_config.py Commit with descriptive message Push and create PR with validation results Processing Patterns Pattern When to Use Batch (multiple APIs → single PR) Same domain, similar structure Iterative (one API at a time) Complex auth, novel patterns Discovery-only (report, no tools) Planning roadmap Validation-only (audit existing) PR review, quality check References Tool templates (Python class + JSON config): references/tool-templates.md Validation & integration guide : references/validation-guide.md