Skip to main content
Glama

generate_data_entity

Read-only

WHEN: developer needs to CREATE a data entity (AxDataEntityView) AOT XML from a table for OData/DMF/data migration. Triggers: 'create data entity', 'generate entity', 'créer une data entity', 'exposer table via OData', 'DMF entity', 'entity for OData', 'entité de données', 'générer entity XML', 'AxDataEntityView pour', 'data entity from table'. Produces complete AxDataEntityView AOT XML with data sources, field mappings, entity key, IsPublic/PublicEntityName for OData, staging table template. Uses real field names and relations from the local custom model. ALWAYS call find_entity_for_table first to verify a standard entity doesn't already exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoOptional: specific fields to include (comma-separated). All fields if not specified.
isPublicNoWhether the entity should be available via OData (default: true)
tableNameYesPrimary table name, e.g. 'SalesTable', 'CustTable'
entityNameYesDesired entity name, e.g. 'ALMSalesOrderEntity'
joinTablesNoOptional: additional tables to join (comma-separated), e.g. 'CustTable,InventDim'
publicEntityNameNoOptional: OData collection name (e.g. 'SalesOrders'). Auto-generated if not provided.

TDQS

A4.3/5.0
Behavior4/5

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

With readOnlyHint=true already signaling no mutation, the description adds meaningful behavioral context by detailing what is produced: complete AxDataEntityView XML with data sources, field mappings, entity key, IsPublic/PublicEntityName, and staging table template. It also notes the use of real field names and relations from the local model.

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 front-loaded with the WHEN trigger, then output details, then the critical prerequisite. The trigger phrase list is long but serves a useful routing purpose; overall, every sentence contributes information without meaningless filler.

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

Completeness4/5

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

For a 6-parameter tool with no output schema, the description covers the artifact produced, its contents, the source model, and the mandatory pre-check. It is sufficient for correct invocation, though it could add a note about what happens if a standard entity already exists.

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 description coverage is 100%, so the input schema already documents all six parameters well. The description adds some context around IsPublic/PublicEntityName and field mappings, but it does not materially extend the schema's parameter-level explanations.

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 tool generates AxDataEntityView AOT XML from a table for OData/DMF/data migration, with a specific resource and output type. It also differentiates this from siblings like get_data_entity_info and create_aot_object by naming the exact XML artifact and use case.

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

Usage Guidelines5/5

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

The description explicitly states WHEN to use it, provides concrete trigger phrases, and instructs 'ALWAYS call find_entity_for_table first to verify a standard entity doesn't already exist.' This gives clear routing and an explicit alternative/check before using the tool.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes and clear triggers, reducing ambiguity. For example, PR-related tools are separated into analysis, listing, commenting, and dependency mapping. However, some overlap exists between find_references, find_extensions, and find_callers, which could confuse an agent without careful descriptions.

Naming Consistency4/5

Tool names follow a consistent snake_case pattern with verb_noun structure within subgroups (e.g., ado_*, find_*, search_*, generate_*). There is no mixing of camelCase or other styles, though the variety of prefixes slightly reduces predictability.

Tool Count3/5

With 38 tools, the server feels slightly over-scoped for its domain. While each tool has a specific function, the number is high compared to typical well-scoped servers (10-15 tools). Some tools like find_references and find_callers could be consolidated.

Completeness4/5

The tool set covers a broad range of D365 F&O development and DevOps tasks, including code search, analysis, security, performance, upgrades, and work item management. Minor gaps exist, such as the absence of direct object modification or batch job management, but the core workflows are well covered.