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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds two real behavioral facts beyond the annotations — the history start date (October 3, 2026) and that coverage varies by dataset — which an agent would otherwise not know, but omits what happens for out-of-range days or partial-coverage days, which is the follow-on question this caveat invites.

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?

Three short sentences with no filler; the datasets and the days_available cross-reference are front-loaded. The only weakness is that the lead sentence is a bare list with no verb, so it reads as a fragment rather than a definition.

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, so the description carries the burden of explaining what comes back; listing the four dataset groups partially does that but says nothing about response shape, granularity, or whether empty/partial days return sparse or error results. For a two-parameter read tool this is adequate but leaves real gaps.

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 50%: 'day' is documented in the schema, while 'api_key' is undocumented (though its 27-char constraint and name make it self-evident). The description's pointer to days_available meaningfully aids selection of a valid 'day' value, which is the only non-trivial parameter, so baseline 3 is appropriate.

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 enumerates the datasets included (graduation stats, 10-minute buyers, dev-share bands, touched outcome distributions) but never states a verb or a coherent one-line purpose — it's a noun-phrase list rather than 'Get the full per-day snapshot for X'. An agent can infer it's a per-day aggregate report, but separating it from the sibling graduation_stats requires guessing.

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 gives one concrete routing rule — 'Use days_available for the exported UTC day range' — which is genuinely useful and names the correct sibling. However, it offers no guidance on when to prefer this over graduation_stats or wallet_day, which are the closest overlapping siblings, so usage is only partially disambiguated.

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