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

Annotations already define read-only, idempotent, non-destructive behavior. The description adds value by specifying the exact return contents (field schema, record count, description) and the sequencing dependency on query, which is behavioral context beyond the annotations. No contradiction.

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?

A single, front-loaded sentence delivers the core purpose, contents, and usage guidance without any filler. Every word earns its place, and the most important info appears first.

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 simple read-only metadata tool with one parameter, the description covers purpose, usage, return contents, and workflow timing. It doesn't discuss error cases or invalid IDs, but those are minor for this straightforward operation and the schema covers the required parameter.

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 100%, and the parameter dataset_id is already documented as coming from search_datasets. The description doesn't add parameter-specific details beyond that, but the schema handles it, so baseline 3 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 states the exact action ('Get metadata') and resource ('one Qatar government open data dataset'), listing specific contents (field schema with English/Arabic labels, record count, description). It clearly distinguishes from search-based siblings by focusing on a single dataset's metadata, not discovery.

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?

Explicitly directs the agent to 'call before query to learn the column names', establishing a clear workflow position. It does not mention when not to use it or name alternatives explicitly, but the pre-query directive is strong context.

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