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

Annotations are all false and provide little guidance, so the description carries the burden of behavioral disclosure. It does communicate that the action mutates state by closing a branch and that the branch may be abandoned. However, it does not explain side effects, whether closure is reversible, or what statuses are recorded, leaving meaningful behavioral gaps.

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?

One tight sentence that front-loads the action and outcome. Every part earns its place, and there is no redundant restatement of the tool name or schema content.

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?

For a tool with 8 parameters, no output schema, and sparse annotations, the description gives the core scenario but omits details about how the statuses should be supplied, what closing implies for the research run, and what a successful closure returns or confirms. The schema fills many gaps, but the overall definition is only minimally complete for such a state-changing lifecycle action.

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 coverage is 75%, so descriptions already exist for rationale, protocolId, caseStudyId, hypothesisId, researchRunId, and mcpIdempotencyKey. The tool description adds slight semantic value by implying that protocolId and hypothesisId default to active items and that statuses relate to evidence outcomes, but it does not meaningfully detail the status enums or the idempotency requirement.

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 uses a specific verb ('Close') with a clear resource ('research hypothesis/protocol') and a precise condition ('after evidence supports, falsifies, or abandons the branch'). This clearly distinguishes it from creation and analysis siblings like create_research_hypothesis or analyze_signal_audit.

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 states when to use the tool: after evidence supports, falsifies, or abandons a branch. It also clarifies that it applies to the 'active or specified' hypothesis/protocol, giving enough context for correct selection among lifecycle tools. It does not explicitly name alternatives or exclusion cases, so it falls short of a 5.

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