get_dataset_metadata

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

No annotations are provided, so the description carries the full burden. It uses the non-mutating verb 'Get' and clearly describes the output (filters, indicators, locations, time periods), which implies a read-only discovery operation. However, it does not explicitly state that it has no side effects or mention any rate limits/auth needs, which would be additional useful context.

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 only two sentences, both of which provide essential value: the first states the tool's output; the second explains its role in the workflow and gives concrete examples (e.g., 'absence rate, number of exclusions'). There is no fluff or repetition.

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?

With a single parameter, no output schema, and no annotations, the description covers all necessary aspects: what it returns (filters, indicators, etc.), why it is needed (to obtain IDs for query_dataset), and when to use it (before querying). It is fully sufficient for an agent to select and invoke the tool 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?

The schema description for dataset_id already provides the semantic context ('Dataset ID from get_publication_datasets'), achieving 100% coverage. The tool description does not add further detail about the parameter beyond that, so it relies on the schema as baseline.

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 what the tool does with a specific verb ('Get') and the resource ('available filters, indicators, geographic levels, locations, and time periods for a DfE dataset'). It also distinguishes itself from the sibling query_dataset by explaining that it provides the IDs needed for that tool.

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 says 'Use this to discover what data is available and what filter/indicator IDs to use with query_dataset' and 'This is essential before querying'. This provides clear when-to-use guidance and names the downstream tool, effectively differentiating it from alternatives.

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