compare_modelsCompare 2-5 AI models side by side on price, speed, and benchmarks. Resolve 'X or Y' questions with a single call.
2-5 modeli yan yana koyar (fiyat, hız, benchmark'lar). 'X mi Y mi' sorularının tek çağrılık cevabı.
| Name | Required | Description | Default |
|---|---|---|---|
| slugs | Yes | ||
| force_refresh | No |
| Name | Required | Description | Default |
|---|---|---|---|
| meta | Yes | ||
| models | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and side-effect expectations. The description adds value by specifying the comparison dimensions (price, speed, benchmarks) and the model-count constraint, but does not detail edge-case behavior like handling more than 5 slugs, which is acceptable given the 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 short, front-loaded sentences with no filler. It states the core action, the comparison fields, and the intended use case in minimal words, making it highly efficient for an agent to parse.
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?
With an output schema present, return-value documentation is handled elsewhere. The description adequately covers the tool's purpose, usage scenario, and model-count range. The main gap is the unexplained 'force_refresh' parameter, but given the moderate complexity and existing annotations, the definition is nearly complete.
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 description must compensate. It does clarify the 'slugs' parameter by constraining it to 2-5 models, but it completely omits the 'force_refresh' parameter, leaving its purpose and effect undocumented. This partial coverage earns a mid-range score.
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 compares 2-5 models side by side across price, speed, and benchmarks, and positions it as the one-call answer to 'X or Y' questions. This verb+resource combination distinctly separates it from siblings like list_models and get_model, which focus on enumeration or single-model details.
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?
It explicitly frames the usage as answering 'X or Y' questions, giving a clear context for when to invoke this tool. However, it does not explicitly name alternatives or state when not to use it, leaving some inference for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.