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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), so the description only needs to add context — and it does: the data comes from public manifests, history begins October 3, 2026, and coverage varies by dataset. That coverage caveat is genuinely useful for interpreting sparse results. It stops short of describing pagination or ordering.

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, front-loaded with what is returned and immediately followed by the coverage caveat. The final sentence is largely redundant with the opening and could be dropped or replaced with real usage guidance.

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 and no parameters, the description carries the return-value burden and does so adequately by naming both returned fields and the per-dataset grouping. The history start date and varying coverage round out what an agent needs to interpret an empty or partial result.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description's mention of per-dataset scope correctly signals that the output is keyed by dataset even though no input selects one.

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 resource and payload: exported UTC days plus byte sizes per dataset, sourced from public manifests. An agent knows exactly what it gets back. It does not, however, contrast itself with siblings like day_full_stats or wallet_day, which also deal with day-scoped data.

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 only usage sentence, 'Use days_available for the exported UTC day range,' just restates the tool name and adds no decision criteria. There is no guidance on when to call this versus day_full_stats, data_preview, or wallet_day, and no stated prerequisite (e.g., call this first to discover valid days).

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