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

Annotations already indicate readOnly/non-destructive behavior; the description adds meaningful context beyond that: multi-source consensus, boolean resolution, ML-DSA-65 signed receipt verifiable on Base, cost, and supported sports. There is 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?

The first three sentences are focused and informative, covering purpose, mechanism, and intended use. However, the pricing appears twice in '$0.50. $0.50 USDC per call,' which is redundant and slightly distracts from the otherwise tight structure.

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's mention of a boolean result with a signed receipt is helpful but incomplete. It omits important operational details such as failure behavior when consensus is not reached, output delivery format, and it fails to mention tennis despite tennis_atp being in the sport enum.

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 0%, yet the description only partially compensates by naming the resolve_for values and sports categories. It does not explain home_team, away_team, game_date, or optional competition semantics, leaving agents to infer meaning from names and patterns alone.

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?

Description opens with 'Binary prediction market resolver for sports outcomes,' clearly naming the resource and behavior. It details the specific conditions it evaluates (home_win, away_win, draw, not_draw) and distinguishes itself from generic sports score or verification siblings via on-chain settlement and signed receipt.

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?

It provides a concrete use case: resolving binary sports prediction markets with a receipt for autonomous on-chain settlement. It does not explicitly name alternatives or exclusion conditions, but the context is clear enough to guide an agent toward appropriate usage.

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