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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: unauthenticated callers see only a public cutoff, authenticated callers additionally receive their own frozen forecast, and all other forecasts stay private until aggregate scoring. This visibility/auth nuance is valuable.

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?

A single front-loaded sentence with no filler. It is efficient, though the compressed jargon clauses mean brevity comes at some cost to immediate comprehension.

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 single-parameter read with no output schema, the description meaningfully explains what is returned (public cutoff plus the caller's own frozen forecast) and the visibility rules. The main residual gap is the absence of any usage routing against the sibling predict tool.

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?

With one parameter at 100% schema coverage, the schema fully documents 'claimId'. The description does not add any meaning to the parameter (e.g., what 'active claim' implies or what an invalid ID yields), so the baseline of 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 indicates it reads forecast/visibility data for a claim, but the vocabulary ('public forecast cutoff', 'frozen forecast', 'aggregate scoring') is domain jargon that makes it hard to state plainly what is returned. It also fails to distinguish itself from the closely related 'morrowkin_predict_claim' sibling. The resource is identifiable but the verb/outcome is muddled.

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?

There is no explicit when-to-use, when-not-to-use, or alternative. The adjacent 'morrowkin_predict_claim' tool (submitting a forecast) is never referenced, so an agent gets no routing help between reading vs writing forecasts. Only implied usage.

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