top_rated

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose the value scale nuance (single-word lexicon entries use a different scale and are excluded unless kind='word'), which is useful. However, it doesn't describe default behaviors like the min_score=2 gate, the include_hidden/include_restricted defaults, the limit cap, or the source override behavior — all of which meaningfully affect what gets returned.

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, focused sentence that states purpose and the key exception in one breath. Efficient and front-loaded with the essential fact. Minor opportunity: it could note the default gate values, but the sentence is well-constructed and wastes no 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?

With 6 parameters, no output schema, and no annotations, the description leaves gaps on default behavior (min_score filter, hidden/restricted exclusions, limit cap, source override priority). The kind='word' exception is the one piece of nuance disclosed. For a listing tool with array of defaults, the description is adequate but doesn't fully orient the agent on what makes results appear or disappear from the listing.

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 100%, so the schema documents all 6 parameters well. The description adds marginal value by explaining the special-case exclusion rule tied to kind='word', which supplements the schema's bare enum list. Since coverage is high, the description doesn't need to re-document parameters; credit for the one meaningful extra it does provide.

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 states a clear purpose: returns the highest human-rated lines in the corpus, with a noteworthy exclusion for single-word lexicon entries unless kind='word'. It identifies the resource (highest-rated lines) and a distinguishing condition. However, it doesn't explicitly differentiate from siblings like search_humor or preference_pairs, relying instead on the inherent uniqueness of a 'top rated' listing.

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 usage context (fetching top-rated content) but provides no explicit guidance on when to use this vs alternatives like search_humor, taste_profile, or preference_pairs. The kind parameter hints at different categories but the description doesn't articulate when this tool is the right choice over sibling tools.

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