Poll the status of a DMF import/export execution by its executionId (e.g. NotRun, Executing, Succeeded, PartiallySucceeded, Failed). For a completed export, also returns the download URL.
| Name | Required | Description | Default |
|---|---|---|---|
| executionId | Yes | The executionId returned by dmf_import_file or dmf_export_package. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It clearly conveys a non-mutating polling operation, enumerates the possible status values, and discloses extra return behavior for completed exports (download URL). It does not explicitly state 'read-only' or describe failure handling, but 'Poll the status' sufficiently implies the safety profile.
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 two concise sentences with no filler. The core action and the key identifier are front-loaded, followed by the useful status examples and the download URL detail. 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 simple single-parameter polling tool with no output schema, the description provides enough context: what to provide, what statuses to expect, and a special return case. It could arguably mention that the executionId must come from a prior DMF operation, but the schema already supplies that dependency, so the overall definition is complete enough.
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?
Schema description coverage is 100% and the only parameter, executionId, is already described as the ID returned by dmf_import_file or dmf_export_package. The description's mention of 'executionId' adds no new semantic detail beyond the schema, so the baseline score of 3 is appropriate.
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 ('Poll') and resource ('a DMF import/export execution'), and identifies the required identifier ('executionId'). It also includes concrete status examples and a distinctive note about the download URL, making it easy to distinguish from sibling DMF tools like dmf_import_file and dmf_export_package.
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 clearly implies the tool is for checking the outcome of a prior import/export operation, especially with the schema noting that executionId comes from dmf_import_file or dmf_export_package. It does not explicitly name alternatives or state 'use this instead of X', but the polling purpose is unambiguous enough for correct tool selection.
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.