yimu-mcp

parse_bill_text

parse_bill_text

Convert raw bookkeeping text, such as 'lunch 25 yuan dining', into structured bill information for automated ledger recording.

Instructions

解析记账原始文本（GET /bill/analysisBillInfoT/{userId}/{text}），返回结构化账单信息。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "parse_bill_text"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes	原始记账文本，如「午饭 25 元餐饮」
`user_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.2Sep 15, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It discloses the HTTP GET method and that the tool returns structured data, implying a non-destructive read, but it does not mention authentication, error cases, or response shape.

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

Conciseness5/5

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

A single front-loaded sentence states the action, endpoint, and result with no redundant words; the raw-text example is already in the schema and not repeated.

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

Completeness3/5

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

The tool is simple and the description covers action, input, and endpoint, but without an output schema it leaves 'structured bill information' vague, and no usage or error context is provided.

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 coverage is only 50%: text is documented, user_id is not. The description's endpoint path at least exposes the existence of userId and links text to raw input, but it does not explain user_id semantics or compensate fully for the missing schema documentation.

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 uses a specific verb ('解析'/parse) and resource (raw bookkeeping text), names the exact GET endpoint, and states the output (structured bill info). This clearly differentiates it from save_bill and other sibling write tools.

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?

The description implies the tool is for converting raw text into structured bill data, but it does not state when to choose it over alternatives (e.g., save_bill/save_bills) or mention any prerequisites/exclusions.

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