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OpenAny

Case Semantic Search API

yuandian_post_open_case_vector_search

Performs semantic similarity search in the case database using a natural-language query. By default, searches both ordinary and authoritative cases. wenshu_filter supports filters such as case category, cause of action, document type, court, region, closing date, and typical cases. Returns complete case content that has been organized for presentation, which is not equivalent to the verbatim full text of the original court document, together with similarity scores. Uses the caller's OpenAny gateway credentials. Charges and authorization are determined by the gateway.

Input Schema

NameRequiredDescriptionDefault
queryYesQuestion or query text to search for
return_numNoNumber of cases to return (default 45; cannot exceed the total number retrieved)
rewrite_flagNoWhether to rewrite the query; defaults to `false`
wenshu_filterNoCase search filters; see the field descriptions for details

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden and does notable work: it explains that returned content is presentation-organized and not the verbatim original document, that similarity scores are included, and that charging/authorization are governed by the OpenAny gateway credentials. Missing only latency or rate-limit characteristics, which keeps it short of a 5.

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

Conciseness4/5

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

The description is front-loaded with the core action and scope before moving to filters, return characteristics, and billing. Five sentences are all substantive, though the billing/credentials sentence could be trimmed without losing agent-relevant information.

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

Completeness4/5

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

With no output schema, the description usefully covers return shape (organized case content plus similarity scores) and the nested filter object's dimensions. It leaves the internal fields of wenshu_filter unspecified by type or enumeration, so an agent knows the categories but not the accepted value formats.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning beyond it: it spells out the filter dimensions inside the nested wenshu_filter object (case category, cause of action, document type, court, region, closing date, typical cases) that the schema only gestures at with 'see the field descriptions for details'. It does not expand on return_num or rewrite_flag semantics.

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

Purpose5/5

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

The description opens with a specific verb and resource ('semantic similarity search in the case database') and immediately clarifies scope ('by default, searches both ordinary and authoritative cases'). An agent can distinguish this from the sibling law-vector-search tools without opening a schema.

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

Usage Guidelines3/5

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

It gives context for default behavior (both ordinary and authoritative cases) and enumerates what wenshu_filter can constrain, which implies when to use it. However, it never names an alternative tool or states when a caller should prefer keyword/case-list searches over semantic search, so the guidance is implied rather than explicit.

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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