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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world). The description adds genuine behavioral context beyond that: the output is descriptive with no causal claims (只描述,不做因果) and the stratification exists to avoid city-center confounding. That interpretive caveat is valuable for how the agent frames results.

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 compact sentences, front-loaded with the core comparison before the stratification rationale. The bilingual restatement is mildly redundant but aids clarity; no sentence is wasted.

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 no output schema, the description should characterize the return shape (per-stratum differences vs a single effect) and it does not. It does establish the analytical scope and a no-causation caveat, and annotations cover safety, but the agent lacks detail on what comes back.

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 metric_a, has_b, and per. The description loosely maps A to metric_a and B to has_b and explains the stratum dimensions, but does not clarify how the 'per' conversion interacts with those strata. Baseline 3 is 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 names a specific analytical verb (compare A between cells with vs without B) and specifies the stratification design (residents × road length, 25 strata). It clearly conveys what the tool computes, though it doesn't explicitly position itself against siblings like compare_change (temporal) or rank.

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 analytical framing but there is no explicit when-to-use, when-not, or named alternative. An agent can infer this is for cross-sectional stratified group comparison, but must reason about when to pick it over compare_change, rank, or overlay_metrics.

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