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

With no annotations, the description carries full burden and does well: it discloses per-call cost, data provenance (pure NG synthesis, no raw third-party data), per-idea-type limit capping, educational disclaimer, and authentication methods. It does not describe response structure or error behavior, but the disclosed traits are substantial.

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 dense and front-loaded with the core purpose, then covers pricing, limit behavior, payment/auth, and disclaimer. It is longer than ideal, but each sentence carries operational value for a paid API with auth requirements.

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 no annotations and no output schema, the description covers the essential invocation context: cost, payment/auth, limit semantics, data source, and non-advice disclaimer. It lacks explicit return-format details and when-to-use guidance, but is otherwise complete for a one-parameter tool.

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 0%, but the description fully compensates for the single 'limit' parameter by explaining that it applies per idea-type and that limit=25 can return up to ~50 total. This adds meaning far beyond the bare schema definition.

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 identifies the tool as returning NG-derived NARRATIVE_SYNTHESIS and CATALYST_CONVERGENCE intelligence, including macro themes, catalyst-convergence events, and confidence scores. This distinguishes it from sibling tools by naming specific idea types, though it lacks an explicit verb like 'retrieves' or 'lists'.

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 for narrative/catalyst intelligence and instructs users to browse tools with get_catalog first, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. The guidance is mostly operational (pricing, payment) rather than comparative.

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