Arithym is an exact math engine for AI agents that provides 62 specialized tools to ensure zero-hallucination arithmetic, calculus, and scientific computations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install arithym-io-arithym
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 arithym-io-arithym 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 Arithym?
Arithym is a high-precision math engine designed to serve as a reliable computation layer for AI agents. By integrating this skill via Openclaw Skills, developers can bypass the inherent limitations of LLMs, such as floating-point drift and logical errors in multi-step arithmetic. It provides a robust Model Context Protocol (MCP) server that grants agents access to exact rational arithmetic, physical constants, and advanced calculus.
Whether your agent is handling financial modeling or complex engineering conversions, Arithym ensures that every numerical output is provably correct. It bridges the gap between natural language reasoning and rigorous mathematical execution, making it an essential addition to any production-grade AI workflow.
Arithym Use Cases
- Financial Modeling: Calculate interest rates, amortization schedules, and currency conversions with absolute precision.
- Scientific Research: Access exact CODATA 2022 values for 254 physics constants and element data without manual lookup.
- Engineering and Physics: Perform complex unit conversions and dimensional analysis while catching errors automatically.
- Symbolic Calculus: Execute derivatives, integrals, and solve for critical points without approximation.
- Large Number Theory: Handle large integer arithmetic, prime factorization, and Greatest Common Divisors (GCD) flawlessly.
How Arithym Works
- Domain Assessment: The agent uses
domain_checkorrecommendto identify the correct mathematical domain for the user's query. - Context Retrieval: If scientific data is required, the agent calls
ep_lookupto fetch exact physical constants or element properties. - Precision Execution: The skill executes the requested computation using specialized tools like
fraction_mathorexact_trigto avoid floating-point errors. - Workspace Management: For multi-step problems, the agent utilizes workspace tools to chain dependent calculations and maintain a logical state.
- Validation: The engine returns the exact result to the agent, ensuring the final response to the user is hallucination-free.
Arithym Setup
To integrate Arithym into your agent environment using Openclaw Skills, update your MCP server configuration with your API key.
- Obtain an API key from the Arithym website.
- Add the following to your
mcpServersconfiguration file:
{
"mcpServers": {
"arithym": {
"url": "https://arithym.xyz/mcp",
"headers": {
"Authorization": "Bearer ${ARITHYM_API_KEY}"
}
}
}
}
- Export your API key in your terminal:
export ARITHYM_API_KEY='your_api_key_here'
Arithym Data Schema & Taxonomy
Arithym organizes its capabilities into distinct functional domains to ensure logical tool selection and data integrity.
| Domain | Primary Tools | Data Handled |
|---|---|---|
| Core Arithmetic | compute, fraction_math, factorize |
Exact integers, rational fractions, square roots. |
| Physical Constants | ep_lookup, ep_query |
CODATA 2022 physics constants, periodic table data. |
| Calculus | graph_derivative, graph_integral |
Derivatives, integrals, Taylor series, and tangent lines. |
| Workspace | field_create, field_update |
Chained calculations and persistent state variables. |
| Units | ep_convert, unit_check |
Physical units (mass, volume, pressure, energy, etc.). |
Arithym Advanced Features
- Zero-Hallucination Calculus: Perform symbolic math including Taylor series and solving for critical points using graph-based tools.
- Automated Dimensional Analysis: Use
scratch_math_unitsto automatically detect and flag dimensional inconsistencies in physics problems. - Workspace State Chaining: Create fields to store and derive data across multiple tool calls, enabling complex, dependent computational workflows.
- Comprehensive Discovery Tools: Use
list_refsandguide_listto help agents self-document and learn which mathematical tools are best for specific tasks. - High-Fidelity Constants: Direct access to the latest scientific constants and element properties ensures accuracy in specialized research fields.
SKILL.md
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