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lint_code

Analyze Python code for errors and style issues using ruff or flake8 to improve code quality and maintainability.

Instructions

Lint a Python file using ruff or flake8

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYesPath to the file to lint
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the linters used but doesn't disclose behavioral traits like whether it modifies files, requires specific environments, outputs results, or has rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operation.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and includes relevant details (Python file, ruff/flake8). Every word earns its place, making it highly concise and well-structured.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete for a tool that likely produces linting results. It doesn't explain what the tool returns, how errors are handled, or dependencies required. For a code analysis tool with rich expected output, this minimal description is inadequate.

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 schema already documents the single parameter 'filepath'. The description adds no additional meaning beyond what the schema provides, such as file format expectations or path examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('lint') and target ('a Python file'), specifying the tools used ('ruff or flake8'). It distinguishes from siblings like 'format_code' or 'analyze_code' by focusing on linting, but doesn't explicitly contrast with them. The purpose is specific but lacks explicit sibling differentiation.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'format_code' or 'analyze_code'. The description implies usage for Python files but doesn't specify prerequisites, constraints, or when-not-to-use scenarios. It's a basic statement of function without contextual direction.

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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