Discover AI prompts

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

Annotations declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), so the bar is lower. The description adds meaningful context beyond annotations: this is asynchronous (a background job requiring polling via get_job) and gated on an active subscription. It does not explain the requestId idempotency contract, hence not a 5.

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?

One dense paragraph of three sentences with no filler; the async/polling instruction is front-loaded after the purpose. It is efficient, though packing purpose, param note, workflow and prerequisite into a single block is slightly heavy.

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 no output schema, the description correctly explains the downstream handoff (get_job → create_tracked_queries) and the subscription gate, which covers the async lifecycle. However, for a 7-parameter tool at 14% schema coverage, it leaves most parameter semantics and the expected format of 'input'/results unexplained, so it is only minimally complete.

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 coverage is only 14% (only requestId is documented in the schema), so the description carries the burden and largely fails: it explains only excludeQueries ('leaves out ones already tracked'). The meaning and format of input, country, language, organizationId and projectId are left entirely undocumented.

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?

States a specific verb+resource with scope: 'Start a background job that proposes the questions people ask AI assistants about a topic in one country - the prompts worth tracking on AI engines.' An agent can distinguish this from discover_keywords and discover_brands from the description alone.

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?

Gives the full operational path: poll get_job for the result, review with the user, then call create_tracked_queries, plus the prerequisite 'Requires an active subscription.' It names the successor tools explicitly and leaves no inference about when to use it.

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