Qingflow MCP (CRUD)

Qingflow Field Resolve

qf_field_resolve

Read-onlyIdempotent

Resolves natural language field names or aliases to stable que_id identifiers for a specified app. Supports fuzzy matching and multiple queries.

Instructions

Resolve natural language field names/aliases into stable que_id mappings for one app.

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": {
      "app_key": "<app_key>"
    },
    "name": "qf_field_resolve"
  }
}

Input Schema

Name	Required	Description	Default
`app_key`	Yes
`query`	No
`queries`	No
`top_k`	No
`fuzzy`	No

Output Schema

Name	Required	Description	Default
`ok`	Yes
`data`	Yes
`meta`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.0May 28, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, which cover safety and repeatability. The description adds that it resolves to 'stable que_id mappings', hinting at deterministic behavior, but does not elaborate on error cases, rate limits, or other nuances. Given the annotations, the description is adequate but not exceptional.

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 a single front-loaded sentence that efficiently conveys the core purpose. It is concise without being vague, but could include more detail without losing conciseness. Every word earns its place, but the brevity leaves gaps in other dimensions.

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?

Despite having output schema, the description lacks essential context for agent decision-making. It does not explain how to use multiple queries, the effect of top_k or fuzzy, or how results are structured. With 5 parameters and no param descriptions, the description is incomplete for proper tool invocation.

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

Parameters1/5

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

The input schema has 5 parameters with 0% schema description coverage, and the tool description provides no additional meaning for any parameter. It does not explain the purpose of 'query', 'queries', 'top_k', or 'fuzzy', nor how they interact. An agent would have no guidance on parameter usage beyond the schema itself, which is insufficient.

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 clearly states the verb 'Resolve' and the resource 'natural language field names/aliases' into 'stable que_id mappings for one app'. It precisely defines the tool's function and differentiates from sibling tools like qf.query.* and qf.records.mutate, which handle queries or mutations rather than field name resolution.

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 should be used when there is an app key and field names to resolve, but it does not explicitly state when to use it versus alternatives like qf_form_get or qf.query.plan. No exclusions or comparisons are provided, so the guidance is only implied.

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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