discover_topics

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

With no annotations provided, the description carries the full burden and does it well. It explains the ranking logic ('breakout > rising > evergreen'), the input constraint (1-5 seeds), and the failure mode ('partial failures reported per seed in errors instead of failing'). This gives the agent clear expectations about side effects and error handling.

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 compact and front-loaded: it identifies the operation, input constraint, output behavior, and error semantics in two sentences. Every clause earns its place, with no fluff or repetition.

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?

An output schema is present, so return-value structure does not need to be spelled out. The description gives the purpose, input shape, ranking semantics, and partial-failure behavior. What's missing is any guidance on how optional parameters affect resultscars, so an agent may not know how to use geo/timeframe/category effectively.

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%, and the description only clarifies seed_keywords (1-5) and that errors are reported per seed. The other five parameters—geo, gprop, category, timeframe, and max_per_seed—are left entirely undocumented in both schema and description. The description does not compensate for the schema's lack of parameter guidance.

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 opens with a specific and complete statement: 'One-shot topic discovery for blog ideation.' It then details the exact input (1-5 seed keywords) and what the tool does with it — pulls trend direction and related queries, then de-duplicates and ranks candidates by breakout > rising > evergreen. This clearly identifies the tool's function and distinguishes it from sibling tools like related_queries or trending_now.

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 a clear use case ('blog ideation') and the input constraint (1-5 seed keywords), but gives no explicit guidance on when to prefer this tool over siblings such as related_queries, trending_now, or interest_over_time. There is a hint of differentiation via 'one-shot' and the ranking behavior, but an agent would have to infer the tool's unique fit.

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