Burs-IA Utils

Inversa de matriz

matrix-inverse

Read-onlyIdempotent

Calcula la inversa de una matriz cuadrada (hasta 20×20); falla si es singular. Cuándo: un resultado numérico tiene que ser exacto o reproducible y no estimado. No para: calcular el determinante de una matriz cuadrada (matrix-determinant). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB.

EN: Computes the inverse of a square matrix (up to 20×20) by Gauss-Jordan elimination; fails for singular matrices. When: a numeric result has to be exact or reproducible instead of estimated. Not for: computing the determinant of a square matrix (matrix-determinant). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB.

Input Schema

Name	Required	Description	Default
`matrix`	Yes	Matrix as array of rows (array of array; required; at least 1 items; up to 20 items).

Output Schema

Name	Required	Description	Default
`inverse`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026

addedInput schema / properties / matrix / examples

Added value: +[
+  [
+    [
+      4,
+      7
+    ],
+    [
+      2,
+      6
+    ]
+  ]
+]

First observedNov 1, 2026

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, but the description adds genuinely new context: the Gauss-Jordan algorithm, failure on singular matrices, determinism guarantee, and concrete resource limits (64 KB input, 1s per call, 1 MB result). Only minor numerical-precision caveats are missing, keeping it just below top.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Content is front-loaded and cleanly structured with When/Not for/Side effects/Deterministic/Limits labels. The Spanish and English duplication inflates length somewhat, but each section earns its place and is easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, read-only numeric tool with an output schema present, the description covers purpose, constraints, failure modes, limits, and side effects. Nothing an agent needs to call it correctly is missing, and return values are covered by the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the single 'matrix' parameter (array of rows, 1–20 items) is fully documented in the schema itself. The description mentions the square-matrix/20×20 constraint but adds little parameter syntax beyond what the schema and examples already convey, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Calcula la inversa de una matriz cuadrada'), the algorithm (Gauss-Jordan), the size limit (20×20), and the failure mode (singular matrices). It also distinguishes itself from the matrix-determinant sibling, so an agent can select it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides 'Cuándo/When' (exact or reproducible numeric result) and 'No para/Not for' with the named alternative matrix-determinant. Both the positive and negative selection conditions are stated, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Burs-IA Utils tools Inspect

Try in Browser

Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?