Yes/no with a probability

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context by clarifying that a probability near 0.5 means equal likelihood, not 'medium' confidence, and by advising one check per label for multiple applicable labels. This goes beyond the annotation coverage, though it does not mention output format or error behavior, which the output schema likely covers.

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 two sentences with no filler. It front-loads the core purpose, then adds a critical interpretation nuance and a usage tip. 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?

With an output schema present, return-value details are covered elsewhere. The description includes the key behavioral clarification about probability interpretation and the multi-label usage note. For a read-only tool with robust annotations and schema coverage, this is sufficient, though it doesn't mention the verdict thresholds or the exact structure of state/question beyond the schema.

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 parameters (state, question, yes_means, no_means, no_at_or_below, yes_at_or_above) are all documented in the schema. The description adds a note about verdict interpretation but does not elaborate on individual parameter usage beyond what the schema provides. Baseline 3 is appropriate since the schema carries the load.

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: 'Ask a yes/no question' and 'Returns the probability that the answer is yes, from 0 to 1, plus a verdict.' This is a specific verb and resource, distinct from the sibling tools (jev_classify, jev_score, etc.) by its focus on binary judgments. However, it does not explicitly contrast itself with alternatives, so it doesn't fully earn a 5.

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 one usage note: 'Use one check per label when several labels may apply at once.' This gives situational guidance but does not explain when to choose this tool over siblings or when not to use it. The guidance is implied rather than explicit, so it falls short of a higher score.

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