zurich_analyze_datasets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering safety. The description adds behavioral context about combining search with analysis and returning structured results plus Markdown report, which is consistent and adds value.

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 concise with two paragraphs and a clear 'Returns:' section. It is front-loaded with purpose. Minor redundancy between first sentence and subsequent explanation, but overall well-structured.

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 the presence of an output schema, the description need not detail return values. It adequately covers purpose, what the tool does, and the nature of output. It could mention that query is required, but the schema covers this. Annotations add openWorldHint. Overall complete for its complexity.

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 input schema has detailed descriptions for all parameters (e.g., query, max_datasets, include_freshness, include_structure), so the description adds little beyond referencing update frequency and field schemas. With high schema coverage, baseline score is appropriate.

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 analyzes datasets comprehensively, focusing on relevance, actuality, and data structure. It combines search with analysis, distinguishing it from sibling tools like zurich_search_datasets (search only) and zurich_get_dataset (single dataset retrieval).

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 notes it is useful for finding available data and assessing its timeliness/completeness, providing clear usage context. It does not explicitly state when not to use or list alternatives, but the context of siblings implies differentiation.

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