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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds genuine context beyond that — data provenance (public data, prediction markets, news), the day-before timing, identical grading — but leaves a real ambiguity about whether a call returns data or a spreadsheet download, which is a behavioral fact an agent needs.

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?

It is a single sentence with no filler, so nothing is wasted outright, but the clause stacking ('each made the day before theirs from public data, prediction markets and the news') makes it harder to parse than a two-clause structure would be. The concrete takeaway is buried in a trailing clause about spreadsheets.

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?

An output schema exists, so return values need not be spelled out, and the tool is low-complexity with one optional parameter and strong annotations. Still, the agent is left unsure what the call actually produces, and the closing spreadsheet remark is ambiguous enough to invite misuse.

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?

There is a single optional parameter with 100% schema description coverage, so the schema fully documents the enumeration of prices and the default board behavior. The description adds nothing about 'target' on top of that, which fits the baseline for fully covered schemas.

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 clearly identifies the resource: a side-by-side board of DataSnack's numbers against big forecasters' published numbers for the same months. It lacks an explicit verb (retrieve? compare? export?) and never states the return form beyond the closing clause, but the subject matter is specific enough to separate it from siblings.

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?

No guidance on when to choose this over related siblings such as scoreboard, calibration, or world, and no exclusions or prerequisites. The only routing hint is the optional 'target' narrowing, and that lives in the schema rather than the description.

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