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

Annotations already establish this as read-only, idempotent, and non-destructive. The description adds useful behavior beyond annotations by specifying the return contents (acquisition datetime and cloud cover) and by providing an example that demonstrates the _apiKey credential format. No behavioral contradiction exists.

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 a single purpose-packed sentence followed by a concrete example. It is front-loaded with the key use case. The example slightly duplicates the schema's example, but it still earns its place by reinforcing the credential format and required parameters.

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 no output schema, the description adequately covers what is returned (scenes with datetime and cloud cover) and how to invoke the tool via example. The parameter schema handles field-level details, and the annotations cover safety. It lacks only explicit guidance about sibling differentiation or potential edge cases, which are minor gaps.

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%, so the schema already documents all parameters. The description's example restates the same parameter values without adding new semantic detail, so a 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 uses a clear subject-verb-resource structure: 'searches the Sentinel-2 catalog (STAC)' and states what is returned: 'matching scenes with acquisition datetime and cloud cover.' This distinguishes it from siblings like sentinelhub_ndvi_stats, which would be about vegetation index analysis, not raw scene availability.

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 opening question, 'Which satellite scenes are available for an area + time,' gives clear context for when to use the tool. It does not explicitly name alternatives or exclusions, but the purpose is specific enough that an agent can identify the right use case without ambiguity.

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