A precision-focused computational skill that connects AI agents to the Wolfram|Alpha LLM API for verified factual and mathematical results.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wolfram-alpha-llm
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install wolfram-alpha-llm using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Wolfram|Alpha LLM API Integration?
The Wolfram|Alpha LLM API skill is a specialized integration designed to bridge the gap between large language models and structured computational knowledge. By delegating complex arithmetic, symbolic math, and factual lookups to Wolfram|Alpha, this skill eliminates common LLM hallucinations and modeling errors. It provides verified evidence-based responses that are formatted specifically for ingestion by AI agents.
As part of the Openclaw Skills ecosystem, this tool allows developers to inject high-fidelity data into their workflows. Whether you are dealing with unit conversions, chemistry constants, or sophisticated calculus, this skill ensures your AI agent operates with the mathematical authority of a world-class computational engine.
Wolfram|Alpha LLM API Integration Use Cases
- Solving complex symbolic equations and calculus problems including integration and differentiation.
- Performing precise unit conversions and physics calculations using specific measurement systems.
- Fetching structured factual data such as demographics, astronomical facts, and chemical properties.
- Executing financial mathematics and currency conversions with real-time data.
- Resolving ambiguous queries through systematic assumptions and localized context parameters.
How Wolfram|Alpha LLM API Integration Works
- The AI agent receives a query requiring precise computation or factual verification.
- The skill translates the user request into a concise, keyword-style English query optimized for the Wolfram|Alpha engine.
- The wrapper script executes an HTTP request to the LLM API, utilizing Bearer token authentication to keep credentials secure.
- Resulting data is cached locally for 7 days to improve performance and reduce API overhead for repetitive queries.
- The skill returns a model-ingestible text string, capped by character limits to ensure the AI agent remains within its context window.
Wolfram|Alpha LLM API Integration Setup
To get started with this Openclaw Skills contribution, ensure you have an active Wolfram|Alpha AppID and Python 3 installed.
# Set your environment variable
export WOLFRAM_APP_ID='your_appid_here'
# Run a test query
python3 skills/wolfram-alpha-llm/scripts/wa_llm.py --input "integrate x^2 from 0 to 5"
Wolfram|Alpha LLM API Integration Data Schema & Taxonomy
The skill manages data through a lightweight caching layer and structured parameter passing to ensure reliability.
| Data Type | Location / Format | Description |
|---|---|---|
| Cache Storage | ~/.cache/openclaw-wolfram-alpha/ |
Stores API responses for 7 days (604,800s TTL) by default. |
| Authentication | HTTP Bearer Header | Ensures the AppID is never exposed in logs or URL parameters. |
| Output Format | Plain Text / Markdown | Concise strings optimized for LLM token efficiency. |
| Input Schema | CLI Arguments | Supports --units, --location, --currency, and --assumption for rich context. |
Wolfram|Alpha LLM API Integration Advanced Features
- Intelligent caching system with configurable TTL to optimize API usage and speed.
- Support for granular localization including latitude/longitude, timezone, and country codes.
- Disambiguation engine using the --assumption flag to handle multi-meaning queries.
- Robust timeout management (scan, parse, and format) for production-grade reliability.
- Custom character budgeting to prevent oversized API responses from exhausting LLM context.
SKILL.md
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