Computes the determinant of a stored square matrix.
Args:
name (str): The name of the matrix.
Returns:
float: The determinant of the matrix.
Raises:
ValueError: If the matrix is not found or is not square.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name of the stored square matrix. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / name / descriptionAdded value: +"Name of the stored square matrix."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only and idempotenthjklmn, but the description adds specific behavior: it raises ValueError when the matrix is not found or not square. That error handling detail goes beyond the structured annotations and is valuable for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core purpose, followed by a standard Args/Returns/Raises block. Every sentence earns its place; no filler or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter read-only operation, the description covers purpose, input, return type, and failure conditions. The presence of an output schema and existing sibling list makes this complete; no critical operating detail is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes `name` as 'Name of the stored square matrix,' and the description restates this almost identically without extra depth (e.g., no naming conventions, accepted formats, or reference requirements). Schema coverage is 100%, so the description adds little beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Computes'), the specific object ('determinant'), the input domain ('stored square matrix'), and the return type. This unambiguously differentiates it from siblings like matrix_inverse or transpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description strongly implies when to use this tool (when you need a matrix's determinant) and includes error conditions, but it does not explicitly contrast with alternative tools or state when not to use it. This is clear context without explicit exclusions or named sibling alternatives.
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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