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// Skill profile

Math & Statistics Graphing Engine

name: mathgraphs

by architectds · published 2026-04-01

数据处理API集成
Total installs
0
Stars
★ 0
Last updated
2026-04
// Install command
$ claw add gh:architectds/architectds-mathgraphs
View on GitHub
// Full documentation

---

name: mathgraphs

version: 1.0.0

description: "Math & statistics graphing, computation, visualization and validation engine"

author: MathTalking

homepage: https://mathtalking.com

mcp_servers:

- url: https://mathtalking.com/api/mcp

transport: streamable-http

tags:

- math

- graphing

- statistics

- visualization

- education

- plot

- geometry

---

# Math & Statistics Graphing Engine

You have access to an interactive math and statistics graphing engine via MCP. It computes and renders results — roots, extrema, intersections, regression, hypothesis tests — on interactive graphs.

When to use this skill

  • User asks to **graph**, **plot**, or **visualize** any math
  • User needs to **verify** a mathematical result visually
  • You computed an answer and want to **show** it, not just describe it
  • Data needs statistical visualization (histogram, regression, distribution fit)
  • Geometry needs precise rendering (triangles, circles, constructions)
  • Tools

    `plot_graph` — Math Visualization

    Plot functions, points, segments, labels, and shapes. Auto-computes roots, extrema, and intersections.

    Element types:

  • `function`: expression like "x^2-4", "sin(x)", "x^2+y^2=1", "(cos(t),sin(t))"
  • `points`: array of {x, y} coordinates with optional label
  • `segment`: line from (x1,y1) to (x2,y2) with optional arrow/dashed
  • `label`: text at position (x, y)
  • `triangle`: three vertices (x1,y1,x2,y2,x3,y3)
  • `box`: edge + height for bar charts
  • `compute_stats` — Descriptive Statistics

    Input: array of numbers. Returns mean, median, std, min, max, quartiles.

    `add_histogram` — Histogram

    Input: array of numbers. Auto-bins and draws bars.

    `add_regression` — Regression

    Input: array of {x,y} points. Fits linear/quadratic/exponential/power. Returns R².

    `fit_distribution` — Distribution Fitting

    Input: array of numbers. Fits normal/uniform/exponential. Returns best fit.

    `test_hypothesis` — Hypothesis Test

    Input: data groups + test type. Returns p-value with visual rejection region.

    Important

  • All tools return an **interactive URL** — always share it with the user
  • The graph is **live**: user can zoom, pan, add functions, adjust sliders
  • Results are **computed from the graph**, not generated — no hallucinated curves
  • Supports 9 languages: en, zh, zh-TW, ja, ko, es, fr, de, pt-BR
  • // Comments
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