validate_monitor_v1_2
Validate Datadog monitor configurations to ensure proper setup and functionality before deployment.
Instructions
Validate the monitor provided in the request.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Validate Datadog monitor configurations to ensure proper setup and functionality before deployment.
Validate the monitor provided in the request.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool validates a monitor but does not disclose behavioral traits such as whether it's read-only or destructive, what validation criteria are used, error handling, or output format. This is a significant gap 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 a single sentence that is concise but under-specified, failing to provide necessary context. While it avoids waste, it lacks front-loaded critical information, making it minimally adequate but not helpful.
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 no annotations, no output schema, and a vague description, the tool is inadequately documented. The description does not explain what validation means, what happens on success/failure, or how it differs from similar tools, leaving the agent with insufficient information to use it correctly.
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 no parameter documentation is needed. The description does not add parameter details, which is appropriate given the schema completeness. Baseline is 4 for zero parameters, as no compensation is required.
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 'Validate the monitor provided in the request' restates the tool name 'validate_monitor_v1_2' with minimal elaboration, making it tautological. It specifies the verb 'validate' and resource 'monitor' but lacks detail on what validation entails or distinguishes it from sibling tools like 'validate_monitor_v1' or 'validate_resources'.
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 does not mention prerequisites, context, or exclusions, leaving the agent with no usage instructions. Sibling tools like 'validate_monitor_v1' and 'validate_resources' exist without differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ClaudioLazaro/mcp-datadog-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server