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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond that: it is 'Keyless', it returns dataset names, titles, tags, and published versions, and it claims authority over the published GFW catalogue. It does not mention rate limits, but for a keyless read-only list that is a minor omission and not a contradiction.

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 front-loaded with the core action and scope, followed by return-value guidance, auth note, and authority claim. The long enumeration of dataset categories is informative rather than filler, though it makes the first sentence slightly heavy. Overall it is tight and every sentence earns its place.

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?

There is no output schema, but the description explicitly states what is returned: dataset name, title, tags, and published versions. Combined with 100% parameter schema coverage and read-only annotations, an agent has enough to select and call this tool correctly, including knowing how to chain results into gfw_dataset or gfw_query.

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%, with page, limit, and query each fully documented in the input schema. The description adds no additional parameter-level semantics beyond what the schema already states, such as default values, bounds, or matching behavior. Baseline 3 is appropriate because the schema carries the full burden here.

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 opens with a specific verb-resource pairing, 'List or keyword-search the Global Forest Watch Data API catalogue', and enumerates the exact dataset categories covered. It also clarifies that returned dataset names feed into gfw_dataset or gfw_query, which distinguishes this catalogue tool from its downstream 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 description tells the agent that this tool is for catalogue discovery and that results should be passed to gfw_dataset or gfw_query, which is clear routing guidance. It also labels itself 'AUTHORITATIVE for what forest-change data GFW actually publishes,' giving a selection rationale. It stops short of explicit when-not conditions, but the downstream references effectively communicate the choice.

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