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 covered. The description adds one genuinely useful behavioral fact — "真实算法引擎执行，非大模型生成" — telling the agent results are deterministically computed rather than LLM-fabricated, but says nothing about output structure, table size, or failure modes.

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?

Very short and front-loaded: the bracketed label identifies the tool, then one sentence covers trigger and return value. No filler, though the fragmentary style with no punctuation between the trigger and the return clause slightly reduces scanability.

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?

With four parameters (two required), no output schema, and a statistical-analysis tool, the description covers what is produced but not the relationship between group_variable and subgroup_variable, nor the role of the optional file_id and variables_to_include. Adequate but leaves real gaps for a multi-parameter analysis tool.

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 every parameter is already documented in the schema, which sets the baseline at 3. The description's only hint, stratifying by "某个变量", loosely maps to subgroup_variable and does not distinguish it from the required group_variable — the main ambiguity an agent would face.

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 output artifact: a Table 1 baseline table stratified by a variable ("按某个变量做分层的基线表"), and the bracketed tag flags it as the subgroup variant, which implicitly separates it from the plain act_table_one sibling. It is clear what is produced, though the sibling is never named explicitly.

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?

Usage is implied by the phrase "用户要按某个变量做分层的基线表" — invoke this when the user wants a baseline table broken out by a stratifying variable. There is no explicit contrast with act_table_one or act_smd_balance, and no stated prerequisites such as needing a valid file_id first.

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