trigger_warning_event

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: pulling simulated LIS data, performing hard rule assessment, prioritizing the rule engine over agent_suggested_level, and recording level_correction in the receipt. It also mentions the return receipt with offset, providing useful transparency without contradictions.

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 appropriately sized, with a summary sentence, a flow diagram, and a behavioral note. It is front-loaded with the main purpose and every sentence adds value, though the flow could be slightly more compact.

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 the presence of an output schema and complete parameter descriptions, the description is sufficient. It explains the tool's role, the full process, and a critical correction behavior, leaving no major gaps in understanding.

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 100%, so the baseline is 3. The description adds some context, especially for agent_suggested_level (used for consistency check and correction) and relates channels to delivery targets, but it does not systematically enrich parameter understanding beyond the schema.

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 generates structured warning messages, sends them to the northbound interface and message queue, and returns a delivery receipt. This is a specific verb+resource+outcome, and it is distinct from sibling tools like list_mock_patients or evaluate_risk_rules, which serve different functions.

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 clear context by outlining the complete flow (pull LIS data -> rule assessment -> assemble message -> deliver -> return receipt), which implies when the tool should be used. However, it does not explicitly specify when not to use it or name alternatives, so it lacks exclusions.

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