MCP Datadog Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates key behavioral traits: pagination ('Results are paginated') and rate limiting ('rate limited to 300 requests per hour'). It doesn't mention authentication requirements, error handling, or response format, but covers important operational constraints adequately for a read-only 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 perfectly concise and well-structured: three sentences that each add distinct value (purpose, pagination note, usage guidance, rate limit). No wasted words, front-loaded with the core purpose. The markdown link for pagination details is appropriately minimal.

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 complexity (search/filtering capability), no annotations, no output schema, and 0 parameters, the description is adequate but has gaps. It mentions pagination and rate limits but doesn't describe the response format, error conditions, or authentication needs. For a search tool that likely returns structured data, more context about outputs would be helpful.

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% description coverage, so the schema already documents that no parameters are required. The description adds value by explaining the tool's purpose involves 'span search query' filtering, which implies some query mechanism exists (likely through the endpoint itself or context). This provides semantic context beyond the empty schema, justifying above baseline.

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 tool's purpose: 'List endpoint returns spans that match a span search query.' It specifies the verb ('List'), resource ('spans'), and scope ('match a span search query'), making it clear what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_spans_events' or 'search_logs_events', which prevents a perfect score.

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 some usage guidance: 'Use this endpoint to build complex spans filtering and search.' This implies when to use it (for complex filtering/search) but doesn't explicitly state when NOT to use it or mention alternatives. No comparison to sibling tools like 'get_spans_events' is provided, leaving the agent to infer usage context.

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