case_hypotheses

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

Annotations provide almost no behavioral signal beyond non-readonly, so the description carries the full burden. It discloses key behaviors: ids are auto-assigned, unregistered ids are refused rather than ignored, statuses are computed from external evidence/gaps, and refuted outranks blocked. This is rich, non-obvious context an agent needs before calling.

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 organized into clearly labeled sections — WHEN, RETURNS, GOTCHAS — and every sentence adds functional value. It is longer than average, but the complexity of the dual read/write behavior and derived-status model justifies the length; nothing feels like filler.

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 no output schema, the description supplies the exact return shape and the meaning of each status. It also explains the refusal behavior for dangling ids and the precedence rule, which are essential for correct use in the broader case-management workflow. The tool is fully usable from the description alone.

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?

Even though schema coverage is 100%, the description adds meaningful semantics: statement is 'one line', omitting it triggers read mode, new hypotheses receive sequential ids, and there is intentionally no status parameter because status is derived. This goes well beyond the schema 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 opens with a precise dual purpose: 'Register a candidate explanation, or read the ledger' with the resource (hypothesis ledger) clearly named. It differentiates itself from siblings by explaining that hypothesis ids are consumed by case_record_gap and case_submit_evidence, making the tool's role in the workflow unmistakable.

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?

WHEN guidance is explicit: use it as soon as a theory is worth testing and again to inspect standings. It also clearly distinguishes the two modes — pass statement to add, omit it to read — and explains how ids connect to sibling tools, so an agent knows exactly when and how to invoke it.

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