MCP Datadog Server

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

With no annotations provided, the description carries full burden but offers limited behavioral insight. It implies a destructive operation ('revoke') that changes access permissions, but doesn't disclose whether this requires specific permissions, is reversible, affects dashboard functionality, or what happens to existing public viewers. 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 a single, efficient sentence that front-loads the core action ('revoke the public URL') and immediately clarifies the outcome ('rendering it private'). Every word serves a purpose with zero redundancy, making it optimally concise while conveying essential 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?

For a zero-parameter mutation tool with no annotations and no output schema, the description provides basic purpose but lacks critical context. It doesn't explain authentication requirements, success/failure responses, or system behavior changes. While concise, it leaves significant gaps about how this tool interacts with the system and what the agent should expect.

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 the schema already fully documents the empty parameter set. The description adds value by explaining the implicit context - the dashboard is identified 'associated with the specified token', suggesting authentication/authorization context rather than explicit parameters. This provides useful semantic context beyond 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 clearly states the verb ('revoke') and resource ('public URL for a dashboard'), specifying that it makes the dashboard private. It distinguishes from generic 'delete' operations by focusing on public access removal rather than dashboard deletion. However, it doesn't explicitly differentiate from sibling tools like 'delete_dashboard' or 'delete_dashboard_public_invitation'.

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 minimal guidance - it mentions the tool operates on 'a dashboard associated with the specified token', but offers no explicit when-to-use criteria, prerequisites, or alternatives. There's no comparison to sibling tools like 'delete_dashboard' or 'update_dashboard_public', 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.