start_hypothesis_verification

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

With no annotations, the description carries the full burden and does add meaningful behavior: the default top_k fallback, the handoff artifact/message concept, and the note about avoiding copying the full transcript. However, it does not disclose side effects such as whether this creates a persistent artifact, whether the verification session is asynchronous, or whether any prior state is overwritten. There is no contradiction with annotations, but the behavioral disclosure is incomplete.

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 well-structured with clear sections for triggers, workflow position, and parameters. The first sentence delivers the core purpose efficiently. Some minor redundancy exists between the trigger bullets and workflow position, but overall each section serves a distinct and useful role without excessive padding.

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 no output schema and no annotations, the description covers the essential invocation details: when to call, what parameters to use, and the default behavior. It is missing only a clarification of what the tool returns or confirms after the handoff, but for a transfer-style action this is a minor gap rather than a critical one. The description is sufficient for an agent to select and call the tool correctly in most cases.

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 0%, so the description must fully compensate, and it does. The dedicated PARAMETERS section explains each of the four parameters in plain language and clarifies the relationship between hypothesis_ids and top_k. It also provides the practical detail that omitted hypothesis_ids triggers top_k-based selection, which the raw schema does not convey.

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?

Description opens with a specific verb and resource: 'Send selected Co-Scientist hypotheses to the verification session.' It clearly distinguishes the tool from related siblings by naming the conceptual 'verification session' and by referencing the workflow with submit_hypothesis. This leaves no ambiguity about what the tool accomplishes.

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 'AUTOMATIC TRIGGERS' section explicitly lists when to call the tool, and the 'WORKFLOW POSITION' states that it should be used after submit_hypothesis has indexed at least one packet. It also explains the default selection behavior when hypothesis_ids is omitted. It lacks explicit when-not-to-use guidance or named alternatives, but the context is strong enough for correct routing.

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