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intel_category

[v1.6.0] 品类全包(肥)。优先用原子工具降 token:intel_category_opportunity / _supply / _demand_pull / _migration。Full category pack. Prefer atomic siblings to cut tokens.

Input Schema

NameRequiredDescriptionDefault
slugNoCategory slug, e.g. optical_module
categoryNoAlias of slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It does add genuine behavioral context that structured fields don't: the pack is 'fat' and expensive in tokens, and atoms should be used to cut cost. It says nothing about read-only vs write, response shape, or size/limits of the payload.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Very short and the cost warning is front-loaded, but the content is duplicated wholesale in Chinese and English and prefixed with a version tag '[v1.6.0]' that adds no selection or invocation value. Roughly half the text is redundant restatement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, no annotations, and optional params, the description is the only place an agent can learn what this aggregate returns — and it never says. Beyond the token-cost hint there is no indication of payload contents, size, or result structure, which is a significant gap for a bundle tool whose whole purpose is returning a lot of data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains slug and its category alias. The description adds nothing about the parameters — it doesn't say whether slug/category are optional filters or what happens when both are supplied (the alias relationship is only in the schema). Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

It conveys that this is the aggregate 'full category pack' as opposed to the atomic pieces, and names the sibling tools it bundles. But '品类全包(肥)' never says what the pack actually contains or what verb the tool performs — it's a noun phrase, not a stated purpose, so an agent knows it is 'everything' without knowing what 'everything' is.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent away from this tool and toward intel_category_opportunity / _supply / _demand_pull / _migration when token budget matters, which is concrete and actionable. It stops short of stating the complementary condition (when to prefer the full pack over the atoms), but the direction is unambiguous.

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

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