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

Annotations already indicate read-only and non-destructive behavior. The description adds meaningful detail about the returned fields, including units (e.g., oracle_velocity as |Δprice|/min) and the nature of the prediction (health_factor, cross_probability). It also notes the distinction between this tool and the full paid model. No contradictions found.

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 somewhat long but well-structured, with a clear list of return fields and a strategic usage note. It front-loads the primary function and then provides actionable guidance. Every sentence contributes value, though the length could be slightly trimmed without losing meaning.

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 there is no output schema, the description adequately enumerates the return values and their meanings. It also situates the tool within the workflow (before submit_bundle) and mentions a premium alternative. It could be more explicit about data freshness or potential inconsistencies, but overall it covers the essential context for an agent to decide when to use the tool.

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 100% for the two parameters, so the baseline is 3. The description adds extra semantics: 'If omitted, returns top 5 candidates by cross probability' and 'Optional protocol filter when borrower is not specified.' This clarifies conditional behavior beyond the schema's simple field descriptions.

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 identifies the tool's purpose: 'Get a structured liquidation probability prediction for a specific borrower or the top candidates.' It specifies the resource (borrower/candidates) and distinguishes it from siblings by calling it 'the core moat tool' that drives bundle decisions. The verb 'Get' is direct and the scope is unambiguous.

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 gives explicit usage context: 'Call this before submit_bundle to confirm the opportunity is still live and to size your bribe correctly.' It also explains behavior when borrower is omitted and mentions an alternative (the paid /intelligence/liquidation-waves endpoint). It doesn't explicitly list exclusions, but the guidance is clear and actionable.

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