dlr_collections

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

With no annotations, the description carries the full behavioral burden; it usefully discloses that no authentication is needed, which is real added context beyond the schema. It says nothing about rate limits, whether the list is static or updated, or what a returned record contains, so an agent cannot predict the response shape beyond 'a list of collections'.

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 core purpose is front-loaded in the first sentence, followed by targeted example utterances and a compact Args block. Every element earns its place for a one-parameter list tool; the examples could be trimmed but they directly aid intent matching.

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 no-auth, single-optional-parameter listing tool with no output schema, the description covers purpose, examples, and the parameter's bounds adequately. The remaining gap is the absence of any hint about the fields in a returned collection or the handoff to dlr_search for follow-up dataset queries.

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 0% and the single parameter has no schema description, but the description fully compensates by documenting the meaning, default (40), and maximum (100) of `limit`. That is everything an agent needs to set the value correctly, short of explaining what happens if you omit it versus hitting the cap.

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?

States a specific verb and resource — returns the list of DLR EOC Earth-observation collections — and names the provider (DLR/German Aerospace Center) plus the caller's likely intent via example Japanese queries. That provider scoping distinguishes it from sibling collection listings like copernicus_collections, inpe_collections, and stac_collections, though it never explicitly points at those siblings.

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 example queries ("German Earth observation data", "DLR's Sentinel-2 collections") imply when the tool is appropriate, and "no authentication required" clarifies a precondition. However, it never states the workflow relationship with dlr_search (list collections here, then search datasets there), so the agent must infer which of the two DLR tools to call.

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