Azure DevOps MCP Server

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

No annotations are provided, so the description carries the full burden. It states the tool lists field names and reference names, which implies a read-only, non-destructive operation, but does not disclose behavioral traits such as permissions required, rate limits, pagination, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 a single, efficient sentence that front-loads the core purpose and adds a practical use case. There is no wasted verbiage, and every word earns its place by clarifying the tool's utility. It is appropriately sized for a simple, parameter-less tool.

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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool does and why it's useful, but lacks details on behavioral aspects like permissions or response structure. For a tool with no structured data beyond the input schema, the description should provide more complete context to guide the agent effectively.

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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description adds value by explaining the output semantics (field names and reference names for custom queries), which compensates for the lack of an output schema. This provides useful context beyond the empty input schema.

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 verb ('List') and resource ('work item field names and their reference names'), with a specific purpose for custom queries. It distinguishes from siblings like 'get_work_item' or 'list_work_items' by focusing on metadata rather than actual work items. However, it doesn't explicitly differentiate from potential similar tools like 'get_work_item_type' or 'get_work_item_types', which might also provide field-related information.

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 implies usage context ('useful for custom queries'), suggesting when this tool might be beneficial. However, it lacks explicit guidance on when to use this vs. alternatives (e.g., 'get_work_item_type' for field details or 'query_work_items' for actual queries), and does not specify prerequisites or exclusions. The implied context is helpful but incomplete for optimal agent decision-making.

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