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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description goes far beyond by detailing the return structure (results with specific fields, facets with counts), the 1,200-char text limit, the limit <=20 cap, sorting options, and the presence of abstracts for Court rulings. It also explains that facets can be used to narrow subsequent searches, providing actionable behavioral context that annotations do not cover.

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 well-structured: a clear opening purpose, then query guidance, then filters, then return values, then next steps. Every sentence adds value—no fluff or repetition. It is appropriately detailed for an 11-parameter tool and front-loads the most critical information (purpose and primary usage) before diving into specifics.

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?

For a complex tool with 11 parameters, no output schema, and no parameter descriptions in the schema, this description is exceptionally complete. It explains all parameters, the exact output format, facet usage, sorting, limits, and even the recommended follow-up action (fetch). An agent has everything needed to call the tool correctly and interpret results without ambiguity.

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%, so the description carries the full burden of parameter documentation. It explains every filter (family, kind, category, sector, topic, published_from/to, document_id, sort, limit) with examples and normalizations, and even advises on query language effectiveness. This fully compensates for the missing schema descriptions and adds meaning beyond the raw titles.

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 ('Find') and a precise resource ('passages in every document Ecuadorian public institutions publish'), and adds the directive 'Start every question here,' which clearly distinguishes it from siblings like catalog, documents, and fetch. An agent knows exactly what this tool does and when to reach for it.

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 explicitly tells the agent to start every question here and to follow up with fetch on the top results, giving clear when-to-use guidance. It does not explicitly contrast with catalog or documents, but the 'start here' instruction strongly implies this is the primary search entry point, which is adequate for selection.

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