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generate_wmilvus_crud

Generate ready-to-run Milvus CRUD code snippets for vector database models using specified fields, model name, and vector dimension.

Instructions

Generate ready-to-run WMilvus CRUD code snippet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoid:str,name:str
model_nameNoVectorEntity
vector_dimNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. "Ready-to-run" hints the output is executable, but it never says whether the snippet is merely returned as text or written to disk, what imports/framework it targets, or any side effects — all things an agent needs before invoking a code generator.

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?

A single front-loaded sentence with zero padding — the intent is delivered immediately. It is appropriately sized in form, though its brevity is partly under-specification rather than true economy.

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?

An output schema exists, so return-value structure need not be restated. But for a three-parameter generation tool with no annotations and no parameter documentation, the definition omits selection criteria, input format, and behavioral expectations — too much is missing for an agent to call it confidently.

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?

All three parameters sit at 0% schema description coverage, and the description mentions none of them. Critically, the colon-delimited syntax of "fields" (only inferable from the default value "id:str,name:str") and the role/units of model_name and vector_dim are explained nowhere, so the agent must guess the expected format.

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

Purpose4/5

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

States a specific verb ("Generate") and resource ("WMilvus CRUD code snippet"), so the agent knows this produces code rather than validating, searching, or deploying. It does not, however, distinguish itself from sibling generators like generate_mcp_client_config or deploy_wmilvus_scaffolding, which is the only thing keeping it from a 5.

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 gives no when-to-use guidance, no prerequisites, and never names an alternative. With siblings such as deploy_wmilvus_scaffolding and generate_mcp_client_config occupying adjacent space, the absence of routing guidance is a real gap.

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