devtu-create-tool

devtu-create-tool is a skill for Claude Code, Codex from mims-harvard/ToolUniverse. It costs 75 tokens per session (1,863 once invoked), scanned A, original, Apache-2.0.

A guide for adding new scientific tools to the ToolUniverse framework, including their Python code, configuration, registration, and tests.

In plain words
What is it for?
Use it to wrap a scientific database or service, add a new API integration, register it with ToolUniverse, and create realistic test examples.
Why use it?
It helps avoid common setup mistakes that leave a tool unloaded, expose an incorrect interface, or fail when tested with real services.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/test_new_tools.py your_tool -v # MANDATORY test.

Good fit Use it to wrap a scientific database or service, add a new API integration, register it with ToolUniverse, and create realistic test examples.

Compare 6 skills from other repositories ↓
About the project

ToolUniverse is a collection of tools, interfaces, and supporting components for building AI systems that perform scientific work. It is for developers creating AI scientist agents that use APIs, databases, machine-learning tools, and domain-specific utilities. The catalogue includes skills, commands, an MCP server, an agent, and a hook for working with the ecosystem.

mims-harvard/ToolUniverse · 1,680 stars · on GitHub · aiscientist.tools

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/mims-harvard/ToolUniverse
agentmods
npx agentmods add skills/mims-harvard/tooluniverse/devtu-create-tool

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for devtu-create-tool

README.md
[![agentmods](https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/devtu-create-tool/github.svg)](https://agentmods.dev/skills/mims-harvard/tooluniverse/devtu-create-tool)
Your own site
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/devtu-create-tool"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/devtu-create-tool/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for devtu-create-tool

Your own site · 80×15
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/devtu-create-tool"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/devtu-create-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,863 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk warn 6 Mar 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 65
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.01863
Opus 5 $0.00037 $0.00932
Sonnet 5 $0.00015 $0.00373
Haiku 4.5 $0.00007 $0.00186

Measured 7d ago against content hash fbbcb3a10032, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

devtu-create-tool scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (templates/api_tool_template.py, templates/simple_tool_template.py, templates/test_template.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get(
skills/devtu-create-tool/SKILL.md · 222 lines

How it starts

The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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)}

Read the full file on GitHub · 222 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 222 lines · 75 tokens per session scan A fbbcb3a10032

Subscribe to this mod's changes

devtu-create-tool is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed 2d ago), licensed Apache-2.0. It adds 75 tokens to every session and 1,863 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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