expand_query_pool

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

The description discloses key behavioral traits: it shows candidates by default and writes only when apply=true, including that each candidate comes with a reason. This is beyond what annotations (none provided) offer. However, it does not disclose potential side effects of writing (e.g., what happens to existing pool entries), rate limits, or authentication needs. For a write-capable tool, this is decent but not exhaustive.

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 concise sentences, front-loaded with the primary purpose and then the key behavioral distinction (default vs apply=true). Every word contributes; no fluff or redundancy. It is well-structured for quick comprehension.

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 tool has 6 parameters, no output schema, and no annotations. The description does not explain the return format (what 'candidates with a reason' means), error handling, prerequisites for writing (e.g., is project_id required?), or the meaning of region. For a complex tool that can write, this is inadequate. It leaves an agent guessing on several critical aspects.

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 description adds meaning to seed (via 'seed-фраза') and apply (via 'записывает при apply=true'), but it does not clarify limit, region, min_freq, or project_id. With schema coverage at 50% (only apply, limit, min_freq have descriptions), the description partially compensates but leaves half the parameters unexplained. It adds some value but not enough to cover the gaps.

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's action: 'Предложить новые запросы в пул отслеживания по seed-фразе через Wordstat' – proposing new queries to the tracking pool based on a seed phrase via Wordstat. It specifies the resource (pool), the input (seed phrase), and the data source (Wordstat), making it distinct from siblings like research_keywords or track_query. No tautology or ambiguity.

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 does not provide any guidance on when to use this tool versus alternatives. It only states the purpose but does not mention exclusions, prerequisites, or contrast with sibling tools such as research_keywords or track_query. An agent must infer the use case from the purpose alone, with no explicit routing.

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