Modify and refresh dashboard configurations in Datadog to maintain current monitoring views and data visualizations.
Update a dashboard
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "update_dashboard_v1"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Update a dashboard' implies a mutation operation, but it doesn't disclose behavioral traits such as required permissions, whether changes are reversible, rate limits, or what the response looks like. This is a significant gap for a mutation 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 extremely concise with 'Update a dashboard', a single sentence that front-loads the core action. There is no wasted text, making it efficient and easy to parse, though this conciseness comes at the cost of detail.
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 as a mutation operation, lack of annotations, no output schema, and 0 parameters, the description is incomplete. It doesn't explain what 'update' entails, potential side effects, or return values, leaving the agent with insufficient information 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 input schema has 0 parameters with 100% description coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but with 0 parameters, the baseline is 4 as it doesn't need to compensate for schema gaps. However, it misses an opportunity to clarify if parameters are implied (e.g., via context like dashboard ID).
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 'Update a dashboard' clearly states the verb ('update') and resource ('dashboard'), providing a basic purpose. However, it lacks specificity about what aspects of a dashboard can be updated and doesn't distinguish this tool from sibling tools like 'update_dashboard' (without '_v1'), making it vague in differentiation.
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 an existing dashboard), exclusions, or compare it to similar tools like 'update_dashboard' or 'create_dashboard_v1', leaving the agent without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.