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

Annotations declare readOnlyHint=true and idempotentHint=true, and the description's 'Deterministically validate' aligns with these. The description adds context about 'current evidence maturity' and the final answer's claims, but it does not disclose behavior like what happens on invalid states, whether it returns a boolean or detailed report, or any rate limits. Since annotations cover the safety profile, a middle score is appropriate; the description could add more behavioral detail but does not contradict the 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 description is a tight, two-sentence block that leads with the core purpose and then gives a specific directive. Every word contributes to understanding the tool's role. There is no fluff or redundancy, and the structure is front-loaded with the key validation action before the usage instruction.

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?

The tool has 8 parameters but only 2 required, and the description covers the main workflow trigger. However, there is no output schema and the description does not mention what the tool returns (e.g., a validation status, error message, or updated state). Since the tool is a gate, knowing the return format would help the agent act on the result. Still, the description and schema together cover parameter usage well, so it is largely complete for a read-only validation 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 description coverage is 100%, so the schema already explains each parameter. The description goes beyond the schema by providing a strategic mapping for the 'state' parameter ('Request production_candidate for paper-ready, trade-ready, production-ready, or execution-validated language'). This adds practical semantic meaning that helps the agent choose the correct enum value, which is genuinely useful and not present in the schema.

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, deterministic validation action on readiness/promotion states, listing the exact claims it gates ('research-validated, risk-validated, paper-ready, production-ready...'). This clearly distinguishes it from the analysis and research-management siblings, which perform different tasks. The verb 'validate' and resource 'readiness state' are unambiguous and tied to a concrete workflow.

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 when-to-use guidance: 'Call this before saying a strategy is research-validated...' It also provides a concrete mapping instruction for when to request production_candidate. This is direct, actionable, and leaves no ambiguity about when to invoke the tool, satisfying the 'when to use' criterion without needing to enumerate alternatives.

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