search_eo_datasets

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

With no annotations, the description carries the full transparency burden. It discloses the two-stage behavior: 'Queries hit the topics map first ... then fall back to keyword matching against live collection metadata'. It also states that 'every hit is classified by sensor modality' and lists the returned dictionary content, giving the agent a clear moidal picture of what will happen after invoking the 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?

The description is compact, front-loaded with the core behavior, then organized into usage guidance and a return block with no repeated information. Each section earns its place, and code-styled references keep the text scannable.

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 search-only tool with two optional parameters, an output schema, and clear sibling routing, the description is complete. It states scope, how the query is interpreted, return fields, and recommended follow-up siblings. Missing details such as pagination or error handling are not needed for correct selection and invocation.

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 covers the parameters at 100%, so the baseline is 3. The description adds meaningful semantic context beyond the schema: it explains the query flows through a topics map and then keyword matching, and that every result is modality-annotated. This complements the schema's free-text and modality descriptions rather than merely repacing them.

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 a clear verb and resource: 'Searches Earth observation DATASETS (STAC collections) by keyword' and clarifies it is a 'collection-level search' on the Earth Search STAC API. It also names the sibling operation `search_eo_scenes` and distinguishes dataset-level discovery from scene-level discovery, making this tool's scope unmistakable.

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 tells the agent when to start here: 'Start here for dataet-level discovery'. It then guides next actions: 'Then use the returned collection ids with search_eo_scenes, or jump staraight to create_geocroissant_from_stac'. This gives clear context for when to use this tool versus its siblings.

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