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

With no annotations to carry the safety/behavior profile, the description goes deep: results are dated observations, not live recomputations; each metric has a status with three possible values; comparability is restricted to a taxonomy epoch; data is append-only; and it's clearly marked pre-operational. This fully compensates for the missing annotations and adds meaningful context an agent needs before trusting the output.

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?

Every sentence earns its place: the purpose is front-loaded, the sibling distinction follows, then parameter usage, pre-operational caveat, status semantics, comparability constraint, and tier availability. Though dense, it is well-organized and omits redundant filler.

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?

Despite no output schema, the description covers return contents, behavioral caveats, parameter options, and the alternative tool. An agent has everything needed to decide whether to call this tool, how to parameterize it, and how to interpret the results — a genuinely complete definition for a complex metrics endpoint.

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 baseline is 3. The description mostly echoes the schema ('Omit metric for all of them') and adds no fundamentally new meaning for either parameter, though it reinforces the append-only behavior of include_history.

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?

Description opens with a specific verb ('Retrieve') and a clearly named resource ('WEO quantitative coordination metrics'), then itemizes the exact metrics returned (CSTF, transmission matrix, FFD, CBCF, growth rate). It also distinguishes itself from get_coverage_stats by contrast, so the agent can tell them apart without inspecting other tools.

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?

Explicitly names the alternative tool and the condition that selects it: 'For live corpus counts and distributions, use get_coverage_stats — metrics here are derived, dated observations, never live recomputations.' It also instructs on parameter usage ('Omit metric for all of them; set include_history for the full append-only series'), leaving no ambiguity about when and how to call.

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