research_benchmark_catalog

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It only indicates the tool returns data, but does not state whether it is read-only, requires authentication, or has any side effects. The 'research-backed' attribute adds some quality context but is insufficient.

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 extremely concise: a single sentence followed by an argument explanation. No extraneous words. Every sentence serves a purpose.

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 has one optional parameter and an output schema (implying return values are documented elsewhere), the description is largely complete. It covers the core function and filter capability. Minor improvement could include mentioning the output format or use cases.

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 parameter description coverage is 0%, so the description must compensate. It adds meaning by explaining task_class is an optional filter and listing example values (coding_agent, tool_use, etc.), but does not provide an exhaustive list or formal enum. This partially bridges the gap.

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 'Return' and the resource 'benchmark catalog', specifying the evaluation dimensions (reasoning, coding, etc.). It also mentions the optional filter, making the tool's purpose unambiguous and distinct from siblings.

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 guidance on when to use this tool versus alternatives (e.g., benchmark_track, calibration tools). It only states the basic function, leaving the agent to infer context. No exclusions or when-not-to-use information is given.

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