mkt_opportunity

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

No annotations are supplied, so the description must carry the full behavioral burden. It does contribute two real claims — the operation is read-only and its output does not constitute proof of purchase intent — which is useful expectation-setting, but it omits ordering/validation failure behavior, side effects, and cost/latency traits for a pipeline that explicitly performs checking.

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?

A single front-loaded clause states the mode of operation, followed by the pipeline order and a scope limitation — no filler. The semicolon-chained structure is dense but every segment carries 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?

Given nested undocumented parameters, no output schema, and no annotations, the description is too thin: an agent cannot construct valid facts/signals payloads or know what the result looks like. The stated pipeline and the purchase-intent caveat are the minimum, but significant gaps remain.

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% and both parameters are required nested structures (facts object, signals object-or-array), so the description must compensate. It only implicitly maps 'semantic_candidates' to signals and 'product facts' to facts, giving no shape, required keys, or accepted formats for either.

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 read-only demand-discovery operation and sketches a pipeline (semantic_candidates → semantic validation → matching against product facts), which is more specific than the bare tool name. However, '需求发现' is an abstract verb-resource pairing, and it never states what the tool returns or how an 'opportunity' differs from what mkt_signal_interpretation or mkt_search produce.

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?

There is no when-to-use guidance and no comparison against any of the dozens of sibling tools; the reader has to infer that this runs before scoring/planning steps. The negative scope note ('不证明购买意愿') hints at a boundary but is not framed as an alternative-selection rule.

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