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

Annotations already declare readOnly, idempotent, non-destructive, closed-world; the description adds useful behavior beyond them by disclosing the append-only registry nature and what each entry contains (advance-stated probability/threshold/date plus resolution and Brier score).

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?

Two sentences, front-loaded with the resource definition and trailing with the usage trigger; dense but no filler, though the long first sentence packs several concepts that could be split.

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, the description usefully enumerates the return fields, and annotations cover the safety profile; the only minor gap is not explaining how status values map to the returned entries.

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 100%, so both parameters (slug, status enum) are already documented with the default and allowed values; the description adds no extra syntax or meaning beyond that baseline.

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 verb (get) and resource (append-only forecast registry of a published future-space) and enumerates the returned content (probability, threshold, date, resolution, Brier score), which cleanly separates it from siblings like get_public_claims and get_public_scenarios.

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?

Gives explicit triggering contexts – questions about DSGHT's forecast reliability or the dated checkable predictions a space makes – but does not name alternative tools or state when to prefer them (e.g. get_public_scenarios).

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