Measured FOMC impact on Bitcoin

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

Annotations already carry readOnlyHint=true and openWorldHint=true, and the description adds meaningful context beyond them: the closing caveat "Description, not prediction" tells the agent these are retrospective statistics rather than forecasts, preventing a whole class of misuse. It also discloses the data provenance ('measured from a minute-resolution record') and the statistical framing ('near a coin flip'). No contradiction with annotations.

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 sentences, each earning its place: the first front-loads usage triggers, the second enumerates return fields, the third delivers the critical epistemic caveat. No filler, no repetition of the title or schema, and the most important routing information comes first.

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?

For a 0-parameter read-only tool with no output schema, the description is fully sufficient: it covers when to call, what data comes back, and how to frame the results. The one thing it omits (exact numeric formatting) is minor against the low complexity and the fact that annotations already cover safety.

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 has zero parameters with 100% schema coverage, so there is nothing to document; the baseline of 4 applies. The description instead productively covers return semantics — per-statement 5/30/60-minute BTC reactions, average move versus a normal half hour, up/down split, and next meeting date — which is the information the agent actually needs.

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 specific trigger scenarios — "what Bitcoin does on Fed days, how FOMC statements move crypto, or when the next FOMC meeting is" — and scopes the resource precisely as measured FOMC impact on Bitcoin. This clearly distinguishes it from the 33 siblings; no other tool in the list is FOMC-specific, so an agent can route correctly without opening schemas.

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 first sentence gives explicit, concrete when-to-use triggers phrased as call conditions. It doesn't name alternatives or say when not to use it, but for a 0-parameter informational tool the three trigger phrases are specific enough to make misrouting unlikely. This matches 'clear context, no exclusions'.

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