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

With no annotations, the description carries the full load and does so well: it discloses determinism, false-positive policy, per-call character cap, session call budget, and the exact shape of the returned issue list. It omits auth/data-retention or whether input is stored, which is the remaining gap.

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?

Front-loaded with purpose and return format, then coverage, then usage rules and limits – a logical progression with dense but purposeful content. The middle enumeration of rule categories is slightly list-heavy but every clause carries operational information.

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?

There is no output schema, so the description correctly compensates by spelling out the逐条 issue-list fields and the no-issue case, plus throughput limits. Complete enough for an agent to call it correctly; only edge-case handling (oversized input, language mismatch) is left implicit.

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 schema already documents both text and lang (including the auto-detection semantics and the zh vs en rule sets). The description's 2000-character note only echoes the schema, so baseline 3 is appropriate – it adds little parameter meaning beyond structured data.

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?

States a specific verb+resource (检查…广告法合规风险) and enumerates the concrete rule families it enforces (第9条绝对化用语、第17/18条医疗功效等). It does not, however, distinguish itself from the sibling check_ai_label, and it frames the scope as Chinese-only even though the schema's lang enum supports English/EU rules.

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?

Provides invocation behavior (同输入必同输出, explicit no-issue reporting, no false positives) and operational limits (2000 chars, 30 calls/session), which is useful. But it never says when to prefer this over check_ai_label or how the two relate, so the when-to-use dimension is only implied.

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