Aman-Amith-Shastry-scientific_computation_mcp

change_basis

Read-onlyIdempotent

    Changes the basis of a stored square matrix.

    Args:
        name (str): Name of the matrix in the tensor store.
        new_basis (list[list[float]]): Columns are new basis vectors.

    Returns:
        Tensor: Representation of the matrix in the new basis.

    Raises:
        ValueError: If the matrix name is not found or non-invertible.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	Name of the stored square matrix to re-express.
`new_basis`	Yes	The new basis as a nested list whose columns are the basis vectors.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 10, 2026

addedInput schema / properties / name / description

Added value: +"Name of the stored square matrix to re-express."

addedInput schema / properties / new_basis / description

Added value: +"The new basis as a nested list whose columns are the basis vectors."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "anyOf": [
+        {
+          "type": "number"
+        },
+        {
+          "items": {
+            "type": "number"
+          },
+          "type": "array"
+        },
+        {
+          "items": {
+            "items": {
+              "type": "number"
+            },
+            "type": "array"
+          },
+          "type": "array"
+        },
+        {
+          "items": {
+            "items": {
+              "items": {
+                "type": "number"
+              },
+              "type": "array"
+            },
+            "type": "array"
+          },
+          "type": "array"
+        }
+      ],
+      "title": "Result"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "change_basisOutput",
+  "type": "object"
+}

First observedJan 31, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavior: it returns a new Tensor representation and raises ValueError for missing or non-invertible matrices, going beyond the structured annotations.

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

Conciseness5/5

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

The description is compact and well-structured with Args, Returns, and Raises sections. Every line conveys useful information without fluff or redundant elaboration.

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

Completeness4/5

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

Given the two simple parameters, full schema coverage, an output schema, and annotations, the description is largely complete for invoking the tool. It includes error conditions and return semantics, though it could clarify the mathematical convention for interpreting new_basis columns.

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 parameters are already well documented. The description mostly restates the schema ('Name of the matrix in the tensor store', 'Columns are new basis vectors') and adds only minor context, not significant new meaning.

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?

The description uses a specific verb and resource: 'Changes the basis of a stored square matrix.' This clearly distinguishes it from sibling tools like determinant, matrix_inverse, or qr_decompose, which perform different operations.

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

Usage Guidelines3/5

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

The intended context is implied: use this when you have a stored square matrix and want it re-expressed in a new basis. However, it provides no explicit guidance about when to prefer this tool over related alternatives, nor does it mention any excluded cases.

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

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