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

With no annotations, the description carries the full burden and does well: it discloses the rolling/auto-resolve behavior, that the response adds current_slug and rolls_to_next_at, and gives the transport, endpoint and price ($0.02 via x402). Minor gaps remain around behavior at unresolved states or latency.

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?

Front-loads the core purpose ('Live probability: ...') and keeps a compact structure, but the same question is restated in the second sentence, which is mild redundancy. The HTTP/pricing footer is dense but informative.

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 parameterless, no-output-schema tool, the description supplies what an agent needs: the recurring question, the evergreen roll-forward semantics, and the extra response fields. It is essentially complete, with only edge-case behavior left unstated.

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?

Zero parameters, so the baseline is 4; the description correctly avoids inventing parameter guidance and instead documents the response-shape additions (current_slug, rolls_to_next_at) that the empty schema cannot convey.

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 recurring question ('Will the next jobs report beat consensus?') with a clear verb-style resource (live probability), which distinguishes it cleanly from siblings like probability_evergreen_next-cpi-above-consensus or next-gdp-print-positive. An agent can pick it out without opening any schema.

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?

Explains when the tool is appropriate through its evergreen semantics: it 'auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence.' That is strong context, but it names no alternatives or exclusion conditions versus the sibling evergreen tools.

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