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 mentions 'query' and data processing, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or output format. This leaves significant gaps for a tool with zero annotation coverage.

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 brief and front-loaded with the core purpose, using two sentences without wasted words. It could be slightly more structured but efficiently conveys key information.

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 of querying scalar values with multiple data sources and formulas, the description is incomplete. No annotations exist, no output schema is provided, and it lacks details on behavior, constraints, or examples. This makes it inadequate for an agent to use the tool 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 with 100% schema description coverage, so no parameter documentation is needed. The description adds value by explaining what the tool queries (scalar values) and its context (widgets, data sources, formulas), which is appropriate given the empty 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 states the tool queries scalar values and mentions widget types (Query Value, Table, Toplist), which provides some specificity. However, it doesn't clearly distinguish this from sibling tools like 'query_timeseries' or 'metrics_query_scalars' that appear to serve similar query functions, making the purpose somewhat vague in 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?

No guidance is provided on when to use this tool versus alternatives. The description mentions support for multiple data sources and processing with formulas, but doesn't specify prerequisites, exclusions, or compare it to similar query tools in the sibling list, leaving usage unclear.

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