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

Despite annotations already indicating readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, the description adds critical behavioral context: 'A bucket is a number only where that network was truly measured; where reach ran out it is null, so a measured zero is always distinguishable from an unobserved gap' and details the 'window_actually_covered block'. These explain output semantics beyond the annotation cues.

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 well-structured and front-loaded: it defines the tool in the first sentence, states the questions it answers, describes return values, then covers null semantics and limitations, finishing with examples. Every sentence adds useful information; no 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?

With 5 parameters and no output schema, the description is remarkably complete. It describes the return shape ('per-bucket count broken out by network, running totals, engagement sums... and an explicit window_actually_covered block'), clarifies coverage gaps, and explains limitations. This gives an agent enough context to invoke and interpret results correctly.

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 baseline is 3. The description's examples (e.g., 'topic "bitcoin", days 7, bucket "day"') mirror the schema's examples and do not add meaning beyond what the schema already provides. The schema itself already explains defaults, caps, and network enum values.

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 'SOCIAL MEDIA VOLUME as a TIME SERIES: how many posts mention a topic, bucketed by day or hour' – a specific verb (count/measure) + resource (posts mentioning a topic) + time-series scope. This clearly distinguishes it from siblings like social_account_activity, which focuses on account activity, not topic volume.

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?

It provides concrete examples ('topic "bitcoin", days 7, bucket "day" for a week-long attention curve') and explicitly states coverage limitations ('X/Twitter is excluded... directional proxy'), which tells the agent when to use it and what to expect. However, it does not explicitly name alternative sibling tools, so it falls short of a 5.

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