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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is known; the description usefully adds that output is an SVG and that it is computed by a real algorithm engine rather than generated by the model, which is genuine trust context. It does not disclose what happens when csv_data is omitted (all parameters are optional), nor any validation or error behavior for malformed CSV.

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?

Two short clauses, front-loaded with the artifact name and return type; nothing is padded. Minor waste comes from repeating the title inside the brackets, and the telegraphic style leaves the sentence without an explicit subject or verb.

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?

The description tells the agent what is produced (an SVG) which partially covers the absence of an output schema. For a computation tool whose only input is a CSV and whose required-field list is empty, the missing piece is a statement of what the CSV must contain and that omitting it is invalid, leaving an agent able to call this with no arguments.

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?

With schema description coverage at 100% and only one parameter, the schema already documents csv_data as 'CSV 文本'. The description adds nothing about expected columns, delimiter, or whether coefficients must be pre-fitted, so it neither compensates for nor enriches the single-parameter interface beyond the baseline.

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 names a specific artifact (nomogram / 列线图) and ties it to a specific input class (Logistic/Cox models), which distinguishes it cleanly from siblings like act_forest_chart, act_roc, or act_km_curve. It is a noun-phrase rather than a full verb+resource sentence, and the bracketed title duplicates the tool title, but an agent can still tell exactly what it produces.

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 clause '用户要把 Logistic/Cox 模型做成列线图' implicitly states the triggering condition, which is real usage context. However, it names no alternatives (e.g., forest chart for coefficient visualization), gives no prerequisites about the CSV needing model coefficients or predictor columns, and offers no when-not guidance.

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