route_task

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions intelligent routing and analysis, but doesn't describe what happens during routing (e.g., does it execute the task, return a recommendation, or proxy to the LLM?), potential limitations, error conditions, or performance characteristics. The behavioral aspects are underspecified.

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 appropriately sized with 4 sentences: purpose statement, elaboration, and parameter explanations. It's front-loaded with the core functionality. The parameter section could be more integrated, but overall it's efficient with minimal waste.

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?

Given 3 parameters with 0% schema coverage, no annotations, but an output schema exists, the description provides basic parameter semantics and purpose. However, for a routing tool with intelligent analysis, it lacks details about the routing logic, return format (though output schema helps), error handling, and how it differs from siblings. It's minimally adequate but has clear gaps.

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 description coverage is 0%, so the schema provides no parameter documentation. The description adds basic meaning for all 3 parameters (prompt as task description, files as context, preferences as routing preferences), but doesn't specify format, constraints, or examples. This provides marginal value beyond the bare 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 tool's purpose: 'Intelligently route a task to the best LLM' and explains it analyzes task characteristics to select appropriate LLM services. It specifies the action (route) and resource (task to LLM), but doesn't explicitly differentiate from sibling tools like 'analyze_parallel' or 'list_services'.

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 implies usage context by mentioning task characteristics analysis and LLM selection criteria (Gemini for large codebases, Qwen for code review), but doesn't explicitly state when to use this tool versus the sibling tools. No clear alternatives or exclusions are provided.

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