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check_code

Analyze MATLAB code for errors and style warnings, providing detailed issue reports with line numbers and severity.

Instructions

Lint MATLAB code using checkcode/mlint.

Writes the code to a temporary file and runs mcp_checkcode() on it, returning a list of issues (line, column, message, severity).

Note: see execute_code above for why the return annotation is CheckResult (not a union with ToolResult).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNo
errorNo
issuesNo
job_idNo
statusYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: writes to a temp file, runs mcp_checkcode(), returns issues. However, it omits details like whether the temp file is cleaned up, required permissions, or side effects. The note about the return type adds context but is confusingly referencing an external 'above' context.

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?

The description is short and mostly to the point, with three clear sentences. The first sentence states the purpose. However, the note about 'execute_code above' is out of context and may confuse readers who don't have that reference. It is otherwise well-structured.

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

Completeness3/5

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

An output schema is present, so return value details are not required. The description explains the process and return type. However, it could include more about the nature of issues (e.g., severity levels) and error handling. The note about the return annotation is helpful for tool designers but less so for agents. Overall, it moderately covers what is needed.

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

Parameters2/5

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

The only parameter, 'code', has no description in the schema (0% coverage). The description implies 'code' should be MATLAB code through context ('Lint MATLAB code') but does not explicitly state the expected format, length constraints, or encoding. This leaves room for ambiguity.

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 clearly states the tool lints MATLAB code using checkcode/mlint. It specifies the process (writing to a temp file, running mcp_checkcode) and distinguishes from siblings, as none of the sibling tools (e.g., cancel_job, get_error_log) perform linting.

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 description does not explicitly state when to use this tool versus alternatives. It implies use for MATLAB code linting but provides no guidance on when not to use or prerequisites. A 3 is adequate but lacks explicit usage boundaries.

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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