MCP Datadog Server

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

No annotations are provided, so the description carries full burden. It states this is a creation/attachment action ('Attach'), implying a mutation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens on failure, or if it modifies existing configurations. The description is minimal and lacks critical operational context for a mutation 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 a single, efficient sentence that front-loads the key action and purpose. It wastes no words and directly communicates the tool's function without redundancy. Every part of the sentence contributes to understanding what the tool does.

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 this is a mutation tool (implied by 'create' in the name and 'Attach' in description) with no annotations and no output schema, the description is inadequate. It doesn't explain what the tool returns, error conditions, or side effects. For a tool that likely modifies cloud infrastructure, more context on behavior and outcomes is needed for safe agent use.

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 with 100% coverage, so there's no parameter documentation burden. The description mentions 'Lambda ARN' and 'AWS account ID' as conceptual inputs, but since no parameters exist, this adds no semantic value beyond the schema. A baseline of 4 is appropriate for zero-parameter tools, as there's nothing to compensate for.

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 ('Attach'), the resource ('Lambda ARN'), and the purpose ('to enable log collection'). It specifies this is for 'Datadog-AWS log collection' and attaches to 'your AWS account ID', making the purpose specific. However, it doesn't explicitly differentiate from sibling tools like 'create_integration_aws_logs_services' or 'create_integration_aws', which might have overlapping functions.

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. It doesn't mention prerequisites (e.g., needing a pre-created Lambda), exclusions, or compare it to sibling tools like 'create_integration_aws_logs_services'. The context is implied but not explicit, leaving the agent to infer usage scenarios.

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