Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add WolframResearch/AgentTools --skill wolfram-alphagit clone --depth 1 https://github.com/WolframResearch/AgentToolsWrote 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.
[](https://agentmods.dev/skills/wolframresearch/agenttools/wolfram-alpha)<a href="https://agentmods.dev/skills/wolframresearch/agenttools/wolfram-alpha"><img src="https://agentmods.dev/badge/skills/wolframresearch/agenttools/wolfram-alpha/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.
<a href="https://agentmods.dev/skills/wolframresearch/agenttools/wolfram-alpha"><img src="https://agentmods.dev/badge/skills/wolframresearch/agenttools/wolfram-alpha.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.00783 |
| Opus 5.5 | $0.00022 | $0.00313 |
| Sonnet 5.5 | $0.00011 | $0.00157 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
wolfram-alpha scanned grade A with 0 findings 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 18d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wolfram|Alpha
Query Wolfram|Alpha for computational answers and retrieve contextual information using semantic search.
Prerequisites
These scripts require wolframscript. If it is not installed or not on your PATH, read references/GetWolframEngine.md (relative to this skill directory) for installation instructions.
Usage
With MCP Server (preferred)
If you have Wolfram|Alpha MCP tools available in your tool list (e.g., mcp__Wolfram__WolframAlpha), use those directly. They provide richer integration and better performance than the bundled scripts.
For a richer experience, consider setting up the Wolfram MCP server. See references/SetUpWolframMCPServer.md (relative to this skill directory) for instructions.
With Bundled Scripts
If no MCP tools are available, use the bundled scripts in the scripts/ directory (relative to this skill directory). Run them with:
wolframscript -f scripts/<ScriptName>.wls <arguments>
Pass --usage to any script to see its argument documentation:
wolframscript -f scripts/<ScriptName>.wls --usage
For detailed usage, arguments, and invocation syntax for each script, see references/Scripts.md (relative to this skill directory).
Reminder: These scripts are only relevant when you do not have the equivalent MCP tool available.
Available Tools
| Script | When to use |
|---|---|
WolframAlphaContext |
Retrieve contextual information about a topic via semantic search |
WolframAlpha |
Query Wolfram|Alpha for computational answers and real-world data |
WolframAlphaContext
Always use WolframAlphaContext as a first step before querying WolframAlpha. It uses semantic search to retrieve relevant background information and helps ensure you have up-to-date context. The context argument should be written in natural language (not as a search query) and be as detailed as possible (up to 250 words).
If your MCP server provides a WolframContext tool, you can use that instead of WolframAlphaContext. It's effectively equivalent, except it may include additional context from Wolfram Language documentation.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 18d ago Changed · -1 lines 3d8e772e46d6
- 1mo ago First seen · 76 lines · 55 tokens per session scan A e932dba802a3
wolfram-alpha is a skill published in the GitHub repository WolframResearch/AgentTools (96 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 783 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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