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

The annotations already establish read-only, non-destructive, closed-world behavior. The description adds meaningful behavioral context by stating that execution uses a real algorithm engine rather than an LLM and that the return is a gating ratio; it still omits error behavior and handling of omitted optional parameters.

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 short and front-loads the tool category and result, with no filler text. The bracketed title duplicates the annotation title, and the fragmentary phrasing slightly reduces clarity.

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 a nested params object, three optional parameters, and no output schema, the description gives only high-level purpose and return type. The schema covers parameters, but the description does not explain accepted event formats, method values, nested parameter structure, or the shape of the gating-ratio output.

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 100%, so the schema already documents events, method, and params. The description adds no parameter-level detail beyond the schema, making the baseline score appropriate.

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 states the resource (flow cytometry gating), the use case (user has flow data needing gating), and the result (gating ratio), so the core purpose is clear. It does not explicitly differentiate from the sibling act_fcs_cluster, which also handles FCS data, so it stops short of a 5.

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 phrase '用户有流式数据要做圈门' gives an implied use case for flow cytometry data requiring gating. However, there is no when-not guidance, prerequisite information, or comparison to alternatives such as act_fcs_cluster.

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