WHEN: you need to know which folder(s) are configured as the workspace/project root for the current caller. Reads D365-Custom-Model-Path and D365-Standard-Model-Path from the request headers or environment variables. Use before any tool that accepts a customModelPath/standardModelPath parameter.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description's job is lighter. It adds transparent context by stating that values are read from request headers or environment variables and names the exact variables involved. It does not describe fallback precedence or behavior when values are absent, so it is not a perfect 5, but it goes beyond the annotations.
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?
Three tight sentences with no fluff. The 'WHEN' use case is front-loaded, followed by the data source and the critical usage directive. Every sentence earns its place.
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?
For a parameterless read-only resolver, the description is nearly complete: it states when to use it, where it reads from, and the intended follow-up usage. The only gap is the lack of an output schema means the exact return shape is not specified, but the description's mention of 'which folder(s) are configured' plus the two named environment variables gives sufficient context.
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 tool has zero parameters, so the baseline of 4 applies. The description still adds semantic value by explaining how this tool's output relates to customModelPath/standardModelPath parameters used by other tools, which helps the agent know why and how to use the result.
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 uses a specific verb ('know which folder(s) are configured') tied to a clear resource ('workspace/project root for the current caller'). It also names the exact configuration sources (D365-Custom-Model-Path and D365-Standard-Model-Path), distinguishing this resolver tool from the many sibling tools that operate on models or paths.
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 opens with a 'WHEN' trigger and explicitly instructs the agent to use this tool before any tool that accepts a customModelPath/standardModelPath parameter. This gives an unambiguous usage rule and context, even though it does not enumerate exclusive alternatives because none are needed for a config-resolution tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.