MCP Datadog Server

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

The description mentions that it 'Returns the span-based metric object from the request body when the request is successful,' which adds some behavioral context about the return value. However, with no annotations provided, the description carries the full burden and fails to disclose critical traits like required permissions, whether this is a mutating operation (implied by 'Create'), error handling, or rate limits. The return statement is helpful but insufficient for a creation tool.

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 sentences, front-loaded with the core purpose ('Create a metric based on your ingested spans in your organization') and followed by a concise statement about the return value. Every sentence adds value, with no redundant or unnecessary information, making it highly efficient and well-structured.

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 complexity (a creation tool with no parameters), no annotations, and no output schema, the description is minimally adequate. It states the purpose and return value, but for a tool that likely involves mutating data in an organization, it lacks details on permissions, side effects, or error conditions. The absence of an output schema means the description's mention of the return object is helpful, but overall completeness is limited.

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 input schema has 0 parameters (schema description coverage is 100%), so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as per the rules for 0 parameters, since the schema fully covers the absence of parameters.

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 action ('Create a metric') and the resource ('based on your ingested spans in your organization'), which is specific and distinguishes it from generic metric creation tools. However, it doesn't explicitly differentiate from sibling tools like 'create_logs_config_metrics' or 'create_rum_config_metrics', which would require mentioning the specific APM (Application Performance Monitoring) context.

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. There are many sibling tools for creating metrics (e.g., create_logs_config_metrics, create_rum_config_metrics), but the description doesn't mention APM-specific context, prerequisites, or when this tool is appropriate compared to others. It only states what it does, not when to use it.

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