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

Beyond the annotations (readOnly, non-destructive, idempotent, closed-world), the description adds billing behavior (valid members read on demand, no trial deduction), membership gating, and the precise semantics of the public_record_matched result field. It also conditions the cross-app jump on the user having opened original_page, all of which an agent could not infer from structured data.

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 trigger condition is front-loaded and each sentence adds distinct information (trigger, input provenance, billing, result semantics, jump restriction). Some sentences are long run-ons with multiple clauses, but none are pure filler.

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 tool has two params, no output schema, and annotations covering safety, and the description covers the missing pieces: input provenance, membership/billing effects, and the meaning of the key result field. What remains thin is the shape/format of the inputs and any behavior for invalid or expired references.

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 0%, so the description must carry the meaning. It successfully establishes that reference is an opaque identifier from a prior 车小花 response that must not be fabricated, and ties quoted_at_ms to the original quote row. It does not clarify the timestamp unit/format or the 28-character reference shape, so it does not fully compensate.

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 opens with an explicit trigger and a specific verb-resource pair: verifying whether a peer used-car quote is still linked to the original listing and whether the original listing's price has changed. This is clearly distinguishable from siblings like compare_quote and search_quotes, which handle comparison and listing rather than linkage verification.

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?

It states when to call (a dealer explicitly wants to check a specific row's linkage/price change) and gives a hard constraint: pass only the reference and quoted_at_ms already returned by 车小花, never guess the ID. It also notes that quotes without an original-listing link are for reference only, implying they are not valid verification targets. No sibling tool is named as an alternative for adjacent needs, which keeps it short of a 5.

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