recommend_model

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

No annotations are provided, so the description bears full responsibility. It states the tool is 'advisory' but does not clarify whether it modifies any data, what permissions are required, or what the output format is. The behavior is vaguely defined.

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 short (two sentences) but lacks critical information about parameters and behavior. Conciseness is not beneficial when it omits essential details.

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 no annotations, no output schema, and no parameter descriptions, the description is highly incomplete. An agent cannot determine inputs, outputs, side effects, or return values from this description alone.

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?

The input schema has 4 parameters with 0% description coverage, and the tool description provides no explanation for any parameter. Terms like planPath, config, repoPath, and alternativesCount are left undefined, severely hindering correct invocation.

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 function: 'Advisory model recommendation based on plan analysis and registry metadata.' It distinguishes from siblings like list_models and get_model_profile by indicating it provides a recommendation rather than just listing or profiling.

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 includes a note that the user must manually select the model in Cursor picker, but provides no guidance on when to use this tool versus alternatives such as list_models or analyze_task. No explicit when-to-use or when-not-to-use criteria are given.

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