compare_modelsHead-to-head between 2-4 models: aggregate ranks, Elo gap with a significance note based on the standard errors, and notable benchmarks they share.
| Name | Required | Description | Default |
|---|---|---|---|
| models | Yes | Two to four model names or slugs. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description fully discloses outputs and mentions a significance calculation. It does not note authentication, rate limits, or side effects, but given the read-only nature of comparisons, it is 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 a single, front-loaded sentence that efficiently conveys purpose and outputs with zero wasted words.
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 description covers the main outputs for a comparison tool. Without an output schema, it sufficiently explains return values. It lacks error handling details, but the tool is simple with one parameter.
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 schema already fully describes the models parameter (100% coverage). The tool description repeats the min/max but adds no new semantic information beyond 'two to four model names or slugs'.
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 specifies a head-to-head comparison of 2-4 models, listing exact outputs (aggregate ranks, Elo gap with significance, notable benchmarks). It clearly distinguishes from sibling tools like get_leaderboard (overall rankings) and get_model (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?
The description implies use when comparing specific models, but does not explicitly state when not to use it or mention alternatives. However, the context of sibling tools makes the purpose clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a unique purpose: general info, model comparison, benchmark details, leaderboard, model details, prediction game, and two search tools. No overlap or ambiguity.
All tool names follow a consistent verb_noun snake_case pattern (e.g., about_the_aggregate, compare_models, get_benchmark). No deviations.
8 tools is an appropriate number for a benchmark aggregation server, covering all necessary functionality without being excessive or sparse.
The tool set covers all major operations for the domain: information, comparison, leaderboard, search, and prediction. No obvious gaps for a read-only aggregate service.