classify_task

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

No annotations are provided, so the description bears the full burden of disclosure. It reveals the translation requirement and confirms the classification behavior, but does not disclose the nature of the output, side effects, or any rate limits. This is minimally adequate.

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 extremely concise: one sentence with a parenthetical example. It is front-loaded with the core purpose and includes essential usage instruction without any fluff.

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?

The tool is simple with 3 parameters and no output schema. The description explains the core purpose and a translation rule, but does not specify what the classification output looks like or any error conditions. It is adequate but could be more thorough.

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?

Schema coverage is 100%, so baseline is 3. The description adds significant value by instructing the agent to translate non-English input for the 'description' parameter, which is a behavioral constraint not present in the schema. This enhances the semantic understanding.

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 tool's purpose: 'Classifies the complexity of a dev task.' It uses a specific verb ('classifies') and resource ('complexity of a dev task'), and the sibling tools (format_plan_block, get_model_suggestions) have distinct purposes, so there is no confusion.

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 provides no guidance on when to use this tool versus its siblings or alternatives. It includes a mandatory instruction about translating non-English input, but does not explain when not to use the tool or any contextual prerequisites.

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