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

No annotations provided; description covers the return content (metadata, distributions, URLs, format, licence) and implies a read operation. It doesn't address authentication, rate limits, or side effects, which is acceptable for a simple fetch tool.

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?

Two sentences, front-loaded with the action, no unnecessary words, and efficient communication of purpose and value.

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 simple tool (1 param, no output schema), the description sufficiently explains what is returned and how it fits into the workflow, making it complete for an AI agent to use correctly.

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 100%; the param 'id' already has a clear description in schema. Description reinforces its origin from search_datasets but adds no further semantic depth beyond the schema.

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 'Fetch full metadata for one dataset by its id' with specific details about contents (distributions, URLs, format, licence) and explains that this is how to find where to actually get the data, distinguishing from siblings like search_datasets.

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?

Description implies using search_datasets first to get the id, and positions this as a step before fetching actual data. It doesn't explicitly name alternatives, but context from sibling tools provides differentiation.

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