Qingflow MCP (CRUD)

Qingflow Value Probe

qf_value_probe

Read-onlyIdempotent

Probe and discover likely field values for a given app field using explicit match modes, returning matched value evidence.

Instructions

Probe likely field values for one app field, with explicit match mode and matched value evidence.

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>",
      "field": "<field>"
    },
    "name": "qf_value_probe"
  }
}

Input Schema

Name	Required	Description	Default
`app_key`	Yes
`field`	Yes
`query`	No
`match_mode`	No
`limit`	No
`scan_max_pages`	No
`page_size`	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

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint true. The description adds behavioral details about match modes and evidence in results, going beyond annotations without contradicting them.

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?

The description is a single, front-loaded sentence with no wasted words. Every element (probe, likely field values, match mode, evidence) adds value.

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 an output schema and annotations, the description is too brief to fully guide an agent. It omits details on how probing works, what evidence looks like, or how parameters interact, leaving gaps for a 7-param tool.

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

Parameters2/5

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

Schema description coverage is 0% with 7 parameters. The description only mentions 'match mode' generally but does not explain other parameters like app_key, field, query, limit, etc., failing to compensate adequately.

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 the specific verb 'probe' to indicate exploratory search, names the resource 'likely field values for one app field', and mentions explicit match modes and matched evidence, which distinguishes it from siblings like qf_field_resolve that may not offer match modes.

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

Usage Guidelines2/5

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

The description does not explicitly state when to use this tool over alternatives like qf_field_resolve or when not to use it. It only implies usage for probing field values, but lacks guidance on context or exclusions.

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

Deploy Server