Parse share links and coupon text to identify products, search across platforms, and produce a cross-platform price comparison report.
解析分享链接/淘口令，自动找全网同款并比价。
从用户分享的文本中提取商品标识 (淘口令/京东链接/拼多多链接)，
查询原品价格，然后跨平台搜索同款，输出比价报告。
Args:
raw_text: 包含商品链接或口令的分享文本
page_size: 每平台取前 N 个同款结果
| Name | Required | Description | Default |
|---|---|---|---|
| raw_text | Yes | ||
| page_size | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden, and it does describe the actual behavior: extracting identifiers, querying the original product price, cross-platform search, and producing a comparison report. It omits edge-case behavior such as unparseable input or unavailable matches, but the core side-effect-free workflow is transparent.
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 description is compact and well-structured: a one-sentence summary, a short workflow expansion, and an Args section. Every sentence adds needed information without redundancy.
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?
For a tool with two simple parameters, an output schema, and no annotations, the description covers the essential input semantics and result concept (比价报告). It only lacks failure-mode and unsupported-input guidance, which would make selection and invocation fully robust.
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 fully compensates by explaining raw_text as the share text containing the link/passcode and page_size as the number of same-product results taken per platform. This adds real meaning beyond the bare type definitions.
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 states a specific verb-resource pair: parse shared text and compare prices across platforms. It names the input types (淘口令/京东链接/拼多多链接) and the workflow (extract identifier, query original price, find same products, output report), which clearly distinguishes it from sibling tools like search_products or compare_prices.
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 clearly establishes the context for use: when the agent receives shared text containing a shopping link or code. It does not explicitly name alternatives or state when not to use this tool relative to siblings, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.