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devtu-create-tool

Build, validate, and test new scientific tools for the ToolUniverse framework.

Install

mkdir -p .claude/skills/devtu-create-tool && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3409" && unzip -o skill.zip -d .claude/skills/devtu-create-tool && rm skill.zip

Installs to .claude/skills/devtu-create-tool

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Create new scientific tools for ToolUniverse framework with proper structure, validation, and testing. Use when users need to add tools to ToolUniverse, implement new API integrations, create tool wrappers for scientific databases/services, expand ToolUniverse capabilities, or follow ToolUniverse contribution guidelines. Supports creating tool classes, JSON configurations, validation, error handling, and test examples.
422 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Intermediate

Key capabilities

  • Register new tool classes with ToolUniverse
  • Generate JSON tool definitions for API wrappers
  • Implement validation logic for tool parameters
  • Create test examples for tool verification
  • Configure tool registration in default_config.py

How it works

The skill guides the creation of a Python class using the @register_tool decorator and a corresponding JSON file to define wrappers, ensuring all registration steps are met.

Inputs & outputs

You give it
API specification and tool requirements
You get back
Registered tool class, JSON configuration, and test suite

When to use devtu-create-tool

  • Create new scientific tools
  • Implement API wrappers for databases
  • Validate tool structure and logic

About this skill

ToolUniverse Tool Creator

Create new scientific tools following established patterns.

Top 7 Mistakes (90% of Failures)

  1. Missing default_config.py Entry — tools silently won't load
  2. Non-nullable Mutually Exclusive Parameters — validation errors (#1 issue in 2026)
  3. Fake test_examples — tests fail, agents get bad examples
  4. Single-level Testing — misses registration bugs
  5. Skipping test_new_tools.py — misses schema/API issues
  6. Tool Names > 55 chars — breaks MCP compatibility
  7. Raising Exceptions — should return error dicts instead

Two-Stage Architecture

Stage 1: Tool Class              Stage 2: Wrappers (Auto-Generated)
@register_tool("MyTool")         MyAPI_list_items()
class MyTool(BaseTool):          MyAPI_search()
    def run(arguments):          MyAPI_get_details()

One class handles multiple operations. JSON defines individual wrappers. Need BOTH.

Three-Step Registration

Step 1: Class registration via @register_tool("MyAPITool")

Step 2 (MOST COMMONLY MISSED): Config registration in default_config.py:

TOOLS_CONFIGS = {
    "my_category": os.path.join(current_dir, "data", "my_category_tools.json"),
}

Step 3: Automatic wrapper generation on tu.load_tools()


Implementation Guide

Files to Create

  • src/tooluniverse/my_api_tool.py — implementation
  • src/tooluniverse/data/my_api_tools.json — tool definitions
  • tests/tools/test_my_api_tool.py — tests

Python Tool Class (Multi-Operation Pattern)

from typing import Dict, Any
from tooluniverse.tool import BaseTool
from tooluniverse.tool_utils import register_tool
import requests

@register_tool("MyAPITool")
class MyAPITool(BaseTool):
    BASE_URL = "https://api.example.com/v1"

    def __init__(self, tool_config):
        super().__init__(tool_config)
        self.parameter = tool_config.get("parameter", {})
        self.required = self.parameter.get("required", [])

    def run(self, arguments: Dict[str, Any]) -> Dict[str, Any]:
        operation = arguments.get("operation")
        if not operation:
            return {"status": "error", "error": "Missing: operation"}
        if operation == "search":
            return self._search(arguments)
        return {"status": "error", "error": f"Unknown: {operation}"}

    def _search(self, arguments: Dict[str, Any]) -> Dict[str, Any]:
        query = arguments.get("query")
        if not query:
            return {"status": "error", "error": "Missing: query"}
        try:
            response = requests.get(
                f"{self.BASE_URL}/search",
                params={"q": query}, timeout=30
            )
            response.raise_for_status()
            data = response.json()
            return {"status": "success", "data": data.get("results", [])}
        except requests.exceptions.Timeout:
            return {"status": "error", "error": "Timeout after 30s"}
        except requests.exceptions.HTTPError as e:
            return {"status": "error", "error": f"HTTP {e.response.status_code}"}
        except Exception as e:
            return {"status": "error", "error": str(e)}

JSON Configuration

[
  {
    "name": "MyAPI_search",
    "class": "MyAPITool",
    "description": "Search items. Returns array of results. Supports Boolean operators. Example: 'protein AND membrane'.",
    "parameter": {
      "type": "object",
      "required": ["operation", "query"],
      "properties": {
        "operation": {"const": "search", "description": "Operation (fixed)"},
        "query": {"type": "string", "description": "Search term"},
        "limit": {"type": ["integer", "null"], "description": "Max results (1-100)"}
      }
    },
    "return_schema": {
      "oneOf": [
        {"type": "object", "properties": {"data": {"type": "array"}}},
        {"type": "object", "properties": {"error": {"type": "string"}}, "required": ["error"]}
      ]
    },
    "test_examples": [{"operation": "search", "query": "protein", "limit": 10}]
  }
]

Critical Requirements

  • return_schema MUST have oneOf: success + error schemas
  • test_examples MUST use real IDs: NO "TEST", "DUMMY", "PLACEHOLDER"
  • Tool name <= 55 chars: {API}_{action}_{target} template
  • Description 150-250 chars: what, format, example, notes
  • NEVER raise in run(): return {"status": "error", "error": "..."}
  • Set timeout on all HTTP requests (30s)
  • Standard response: {"status": "success|error", "data": {...}}

Parameter Design

Mutually Exclusive Parameters (CRITICAL — #1 issue)

When tool accepts EITHER id OR name, BOTH must be nullable:

{
  "id": {"type": ["integer", "null"], "description": "Numeric ID"},
  "name": {"type": ["string", "null"], "description": "Name (alternative to id)"}
}

Without "null", validation fails when user provides only one parameter.

Common cases: id OR name, gene_id OR gene_symbol, any optional filters.

API Key Configuration

Optional keys (tool works without, better with):

{"optional_api_keys": ["NCBI_API_KEY"]}
self.api_key = os.environ.get("NCBI_API_KEY", "")  # Read from env only

Required keys (tool won't work without):

{"required_api_keys": ["NVIDIA_API_KEY"]}

Rules: Never add api_key as tool parameter for optional keys. Use env vars only.


Testing (MANDATORY)

Full guide: references/testing-guide.md

Quick Testing Checklist

  1. Level 1 — Direct class test: import class, call run(), check response
  2. Level 2 — ToolUniverse test: tu.tools.YourTool_op1(...), check registration
  3. Level 3 — Real API test: use real IDs, verify actual responses
  4. MANDATORY — Run python scripts/test_new_tools.py your_tool -v → 0 failures

Verification Script

# Check all 3 registration steps
python3 -c "
import sys; sys.path.insert(0, 'src')
from tooluniverse.tool_registry import get_tool_registry
import tooluniverse.your_tool_module
assert 'YourToolClass' in get_tool_registry(), 'Step 1 FAILED'
from tooluniverse.default_config import TOOLS_CONFIGS
assert 'your_category' in TOOLS_CONFIGS, 'Step 2 FAILED'
from tooluniverse import ToolUniverse
tu = ToolUniverse(); tu.load_tools()
assert hasattr(tu.tools, 'YourCategory_op1'), 'Step 3 FAILED'
print('All 3 steps verified!')
"

Quick Commands

python3 -m json.tool src/tooluniverse/data/your_tools.json     # Validate JSON
python3 -m py_compile src/tooluniverse/your_tool.py             # Check syntax
grep "your_category" src/tooluniverse/default_config.py         # Verify config
python scripts/test_new_tools.py your_tool -v                   # MANDATORY test

References

When not to use it

  • Creating tools that do not follow the multi-operation pattern
  • Adding tools without corresponding JSON definitions

Prerequisites

ToolUniverse framework environment

Limitations

  • Tool names must be 55 characters or fewer
  • Requires return_schema to use oneOf for success and error states

How it compares

It enforces strict structural and validation patterns specific to the ToolUniverse framework rather than generic tool creation.

Compared to similar skills

devtu-create-tool side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
devtu-create-tool (this skill)15moCautionIntermediate
mcp-builder1363moReviewAdvanced
ai-agents-architect56moNo flagsAdvanced
llm-app-patterns36moNo flagsIntermediate

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