ms-fabric-mcp-server

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

With no annotations provided, the description carries full burden but only partially discloses behavior. It explains what the tool does (removing dependency edges) and the conditional logic with from_activity_name, but misses critical details like whether this requires specific permissions, if changes are reversible, potential side effects on pipeline execution, or error handling. For a mutation tool with zero annotation coverage, this is insufficient.

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 efficiently structured with a clear purpose statement, parameter explanations, and return value summary in separate logical sections. Every sentence adds value without redundancy, and it's appropriately sized for the tool's complexity.

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 (4 parameters, mutation operation), no annotations, but with an output schema (returns dictionary with specific fields), the description is reasonably complete. It covers purpose, parameters, and return structure, though it could better address behavioral aspects like permissions or side effects to fully compensate for the lack of annotations.

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 0%, but the description compensates well by explaining all 4 parameters in plain language, clarifying their roles (e.g., workspace_name as 'display name', pipeline_name for 'existing pipeline to update', activity_name as 'being depended on', and from_activity_name's optional filtering effect). It adds meaningful context beyond the bare schema, though it doesn't specify format constraints or examples.

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 specific action ('Remove dependsOn references') and target resource ('to a target activity'), distinguishing it from sibling tools like delete_activity_from_pipeline (which removes the activity itself) and add_activity_to_pipeline (which adds dependencies). The verb 'remove' is precise and the scope is well-defined.

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 through the parameter explanation (e.g., 'If from_activity_name is provided, only removes edges from that activity'), but lacks explicit guidance on when to use this tool versus alternatives like delete_activity_from_pipeline or when dependencies should be removed. No clear exclusions or prerequisites are stated.

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