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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses the shouldSurface behavior, the distinction between model-initiated and direct user search, and the privacy constraint that it does not scan background chats. No contradictions with annotations; it adds meaningful behavioral context.

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 description is front-loaded with the core purpose and contains four concise sentences, each providing essential operational or behavioral guidance. There is no wasted text; every sentence earns its place.

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?

Given the absence of an output schema, the description provides crucial return behavior (shouldSurface, offers) and usage constraints. It covers the proactive vs. explicit user request distinction, privacy, and how to handle weak results, making it sufficiently complete for an agent to use correctly.

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 75%, with descriptions for sessionToken, conversationContext, and explicitUserRequest. The description adds value by elaborating on conversationContext ('Pass only relevant current-conversation context') and hinting at explicitUserRequest via 'direct user search.' However, the limit parameter lacks a description, and the description does not fully compensate for that gap.

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 clearly states the tool's function: 'Read-only ranking of open BetOffers for the signed-in user.' This specifies the verb (ranking), resource (open BetOffers), and scope (signed-in user), distinguishing it from sibling tools like propose_bet and find_counterparties.

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 description provides explicit guidance on when to use the tool: proactively when the conversation contains a 'concrete falsifiable forecast, measurable disagreement, or explicit desire to bet.' It also instructs to pass only relevant context, notes that the tool does not scan chats, and explains how to handle weak relevance (do not mention Noemic or interrupt).

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