Recommend Model Route

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: 'Returns advice only and never switches the active client', confirming the tool's side-effect-free nature. No contradiction with annotations. The description could mention error handling or latency but is sufficient given the strong annotation coverage.

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 two sentences, front-loaded with the key action, and contains no filler. Every word adds value: 'conservative' qualifies the recommendation, 'one task' sets scope, and 'never switches' clarifies behavior. Ideal conciseness.

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 the tool's complexity (7 parameters, output schema exists, good annotations), the description covers the core workflow but leaves out context like the meaning of 'conservative', 'effort', or how the recommendation relates to the input parameters. The output schema might fill gaps, but the description could be more helpful for understanding the tool's role in a multi-step workflow.

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 only 43% (3 of 7 parameters have descriptions). The description adds no parameter-specific information; it only states the overall purpose. Parameters like 'risk', 'current_effort', and 'context_tokens' remain undocumented, and the description does not compensate for the low coverage. The agent must rely on the incomplete schema, which is insufficient.

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 verb 'recommend', the resource ('model and effort'), and the scope ('for one task'). It also distinguishes from the sibling tool 'token_guardian_usage_snapshot' by emphasizing that it returns advice only and does not change state, making the purpose specific and unambiguous.

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 explicit guidance on when to use this tool versus the sibling 'token_guardian_usage_snapshot'. It states that it returns advice only, implying safe usage, but does not mention when to choose recommendations over usage snapshots or any prerequisites or exclusions. This leaves the agent without clear direction on invocation context.

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