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

Annotations already declare readOnly, openWorld, idempotent, and non-desstructive, and the description adds substantial further behavioral context: per-venue status so failures are visible, payment mechanics ('$0.008 USDC per call via x402 on Base'), challenge behavior on unpaid calls, zero cost for no-data calls, and the Kalshi 429 issue. It also provides the equivalent HTTP route. 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?

Every sentence earns its place: purpose and output fields, use case, Kalshi exclusion, cost and payment behavior, HTTP route. It is longer than average but density is high, and the most important information is front-loaded. The structure flows logically from what -> when -> caveats -> cost.

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 monetized cross-venue search tool with no output schema, the description covers return fields, failure semantics, payment flow, cost, and routing. An agent has all information needed to invoke the tool correctly and interpret results, even without seeing anything else.

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%, with each parameter (q, venues, limit_per_venue) already documented with types, defaults, and examples. The description adds no new parameter-level meaning; it mostly restates the purpose. Per the baseline for full schema coverage, 3 is appropriate.

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 opens with a specific verb and resource: 'Find a prediction market by question text across two venues at once', and details the exact normalized output fields. It clearly distinguishes itself from single-venue sibling tools by explicitly saying 'Use it when you know the question but not the venue or the id.'

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 gives an explicit when-to-use condition ('when you know the question but not the venue or the id') and a concrete exclusion ('Kalshi is deliberately not included' with a reason). This effectively instructs the agent to prefer single-venue siblings when the venue is already known, without naming them.

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