search_eu_ai_act

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

With no annotations, description carries full burden but only states it returns matching provisions. Does not disclose search behavior (e.g., whether it's full-text or metadata search, case sensitivity, phrase matching, result limits, or pagination). Minimal behavioral disclosure.

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?

Single sentence is concise and front-loaded with the key action. No unnecessary words.

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?

No output schema; description only says 'Returns matching provisions' without specifying format, structure, or what fields are returned (e.g., article ID, text snippet). Missing information on result set size, pagination, or error handling.

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 provides 100% parameter descriptions, so baseline is 3. The tool description adds no extra meaning beyond what the schema already states for query and language.

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?

Description clearly states the tool performs full-text search on the EU AI Act corpus, including specific document types (Articles, Recitals, Annexes). This distinctly differentiates it from sibling tools like lookup_article (targeted article retrieval) and classify_ai_system (classification).

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?

No guidance on when to use this tool versus alternatives. Does not mention when not to use (e.g., if looking for a specific article by number, lookup_article might be better). Agent has to infer from name and sibling tool names.

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