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

Annotations already cover read-only, idempotent, non-destructive, and closed-world. The description adds meaningful behavioral context: results cite only scope-authorized evidence and weak results are clearly labeled. This goes beyond the annotations without contradicting them, though it stops short of detailing result structure or failure modes.

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 purpose, then usage guidance, then behavioral caveats. No filler or repetition; every clause adds value. This is exemplary conciseness for a tool description.

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 tool's moderate complexity (5 params, no output schema), the description covers purpose, usage exclusions, and key behavioral traits. It does not explain return format or error conditions, but the read-only nature and annotations reduce the need. Largely complete for an AI agent's selection and invocation.

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 coverage is 60% (3 of 5 params described). The description adds semantics for offerId by mentioning 'optionally anchored to an existing draft offer,' which clarifies that parameter. However, 'limit' remains undocumented in both schema and description, and no extra meaning is provided for explicitUserRequest beyond its const:true schema constraint. The description partially compensates but not fully.

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 states a specific verb ('find') and resource ('counterparties' — people for concrete falsifiable forecasts or disagreements), and explicitly distinguishes itself from sibling tools by labeling it 'Secondary' and contrasting with open bets/useful questions. This clearly differentiates from find_relevant_bets and propose_bet.

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?

Explicitly states when to use: when the user asks to find a person for a concrete forecast/disagreement, optionally anchored to an offer. Also provides a strong when-not: 'Do not call proactively' and directs to open bets/useful questions instead. This is clear usage guidance with alternative tools in mind.

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