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convert_cdm_to_ldm

Convert a conceptual data model (CDM) into a logical data model (LDM) using PowerDesigner's native conversion or structured mapping, and receive the new model's details.

Instructions

Convert a CDM model to an LDM. Uses PowerDesigner's native conversion when available, otherwise a structured mapping. Returns the new model info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the PowerDesigner native conversion fallback and return value, but it does not say whether the source model is modified, whether the new LDM is saved or opened, whether the operation is reversible, or what happens on failure.

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 concise and front-loaded with the core purpose. The fallback mapping sentence adds some implementation context, though it is not strictly necessary, and the return-value sentence is useful.

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?

For a conversion tool with no annotations and no output schema, the description is too sparse. It omits key operational context such as side effects on the source model, how the 'new model info' is structured, whether the new model is persisted, and how this compares to the CDM-to-PDM conversion path.

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%, so the description must clarify the model_id parameter, but it never explicitly states that model_id is the CDM model to convert, its required format, or any constraints. The parameter name is self-explanatory to some degree, but the description adds no semantic value beyond the schema.

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 states a clear action ('Convert'), a specific source resource ('CDM model'), and a distinct target ('LDM'). This differentiates it from sibling tools like convert_cdm_to_pdm and convert_ldm_to_pdm based on target model type.

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?

No guidance is given about when to prefer this tool over alternatives, such as convert_cdm_to_pdm or convert_ldm_to_pdm. The description implies the target LDM but does not state conditions, prerequisites, or exclusions.

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