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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context beyond them: the pre-operational caveat, the per-metric `status` vocabulary (published / pre_operational / insufficient_corpus), the taxonomy-epoch comparability constraint, and the derived-not-live distinction. This is the kind of nuance an agent cannot infer from structured fields.

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?

Dense and front-loaded: the return payload is described first, then routing, then behavioral caveats. Some material (the `metric`/`include_history` guidance) duplicates the schema, and the status explanation is slightly repetitive, but there is no filler prose.

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 no output schema, the description carries the return-shape burden and does so: it lists every metric, explains the sparse matrix layout and fixed row order, and documents the `status` field. For a read-only metrics endpoint it leaves no operational gap.

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 100%, so both parameters are already fully documented in the schema. The description largely restates the same semantics (omit `metric` for all; `include_history` for the full series) without adding format or edge-case detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 ('Retrieve the WEO quantitative coordination metrics') and enumerates the exact metric set returned (CSTF, transmission matrix, FFD, CBCF, CGR). It explicitly differentiates itself from the sibling get_coverage_stats, so an agent can route without opening either schema.

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?

Names the alternative tool and the condition that selects it ('For live corpus counts and distributions, use get_coverage_stats'), plus concrete invocation guidance: omit `metric` for all, set `include_history` for the full series. Both the when and the how are covered.

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