Decide between bounded alternatives

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

With no annotations present, the description carries the full behavioral burden and does so thoroughly. It discloses that the tool may return escape hatches (ask_user / investigate / none), that it produces per-candidate per-requirement supported / contradicted / unknown judgments, that it is single-shot, and that high probability from the model is not proof.

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 dense but well organized: it front-loads the intended use case, then states required inputs, explains the output shape, and closes with usage cautions and exclusions. No sentence is wasted; the length is justified by the tool's behavioral complexity.

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?

There is no output schema, so the description correctly explains return values: Choice distribution over candidates, escape hatches, and per-requirement judgments. It also covers operational guardrails (one call per unchanged decision, don't re-run for a pleasing answer) and epistemic framing ('High probability is not proof'). An agent has enough context to invoke and interpret the tool correctly.

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?

The input schema covers 100% of parameters with detailed descriptions, so the baseline is 3. The tool description adds minimal parameter-level meaning beyond the schema, aside from framing how many candidates to supply and the distinction between evidence and priorities, which the schema already addresses.

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?

States a specific verb and resource: decide over bounded alternatives, with a distinctive output of a Choice distribution, escape hatches, and per-requirement judgments. The described use cases (implementation alternatives, product tradeoffs, workflow selection) and output artifacts clearly separate it from siblings like jev_classify, jev_rerank, and jev_compare.

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 says when to use it ('unresolved, bounded decision... semantic judgment over supplied evidence') and when not to ('open-ended research, routine choices, correctness proofs, or predicting user consent'). It also gives alternatives—source inspection, tests, the user, or a reasoning model—and adds the critical 'do not repeat a call to obtain a more pleasing answer' rule.

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