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get_object_context

Read-onlyIdempotent

WHEN: you need a COMPLETE picture of a D365 object in ONE call. Returns in a single response: full structure (fields, method signatures, relation summary) AND all CoC extensions / event handlers -- equivalent to calling get_object_details THEN find_extensions. Use this INSTEAD of those two separate calls to reduce round-trips. Optionally includes best-practice violations (set includeValidation=true). Pass methodName to also include the full body of a specific method. Pass aotType to disambiguate when several AOT objects share the same name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aotTypeNoOptional: AOT type to disambiguate, e.g. 'AxTable', 'AxClass', 'AxForm'.
methodNameNoOptional: specific method name to include full body for.
objectNameYesExact object name, e.g. 'SalesTable', 'CustTable', 'VendInvoiceJour'
includeValidationNoInclude best-practice violations (default false -- adds latency for large objects).

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds meaningful behavior: it consolidates two operations into one response, includes best-practice violations only when requested, and warns that includeValidation adds latency for large objects. This goes beyond the structured metadata.

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 and return summary, then routes to alternatives, then covers optional parameters. It is slightly long but every sentence contributes useful decision or invocation information.

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

Completeness5/5

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

With no output schema, the description carries the burden of explaining what the tool returns, and it does: full structure, method signatures, relation summary, CoC extensions/event handlers, and optional validation data. It also covers all parameter behaviors, making the tool fully callable without external context.

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

Parameters4/5

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

The input schema already describes all four parameters at 100% coverage, so the baseline is 3. The description adds extra value by explaining the effect of each parameter: methodName includes a full method body, aotType disambiguates same-named objects, and includeValidation adds best-practice checks with a latency tradeoff.

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?

Clearly states the tool returns a complete picture of a D365 object in one call, including structure and all CoC extensions/event handlers. It explicitly distinguishes itself from get_object_details and find_extensions, so an agent can tell exactly what this tool offers.

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?

Provides explicit WHEN guidance and names the alternatives: 'Use this INSTEAD of those two separate calls to reduce round-trips.' It also explains when to pass methodName, aotType, and includeValidation, which is actionable selection guidance.

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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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.