Dynamics 365 Finance & Operations MCP Server

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool retrieves labels and returns a dictionary, but lacks critical details: it doesn't mention if this is a read-only operation, potential rate limits, error handling, or authentication requirements. The description covers basic functionality but misses key behavioral aspects needed for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized. It starts with a clear purpose statement, followed by a bullet-point list for args and returns, making it easy to parse. Every sentence adds value without redundancy. Minor improvements could include integrating the purpose more fluidly, but overall it's efficient and front-loaded.

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

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

Given the tool's moderate complexity (batch retrieval with 3 parameters), no annotations, and no output schema, the description is partially complete. It covers the basic operation and parameters but lacks details on output structure (beyond 'dictionary'), error cases, and behavioral constraints. It's adequate as a minimum viable description but has clear gaps for informed tool selection.

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

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

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'labelIds' as a list of IDs to retrieve, 'language' for label texts, 'fallbackToEnglish' for translation fallback, and 'profile' as optional. This compensates well for the schema's lack of descriptions, though it doesn't detail formats or constraints like valid language codes.

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

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

The description clearly states the tool's purpose: 'Get multiple labels in a single request.' It specifies the verb ('Get') and resource ('multiple labels'), and distinguishes it from the sibling tool 'd365fo_get_label' by emphasizing batch retrieval. However, it doesn't explicitly contrast with other siblings like data retrieval tools, keeping it from a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It mentions retrieving multiple labels but doesn't specify scenarios, prerequisites, or comparisons with other tools like 'd365fo_get_label' for single labels or general data retrieval tools. This lack of contextual direction limits its utility for an AI agent.

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