Modify existing Datadog dashboards to reflect current monitoring needs and data visualization requirements.
Update a dashboard using the specified ID.
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"
}
}| 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. It states 'Update' implies a mutation, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
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 with no wasted words. It's front-loaded with the core action ('Update a dashboard'), making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's purpose.
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 an update operation with no annotations, no output schema, and 0 parameters in the input schema, the description is incomplete. It doesn't explain what can be updated, how to provide the ID, what the response contains, or error conditions. For a mutation tool, this leaves critical gaps for an AI agent 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 parameters are documented in the schema. The description mentions 'using the specified ID', implying an ID parameter is needed, but doesn't specify its format or source. Since there are 0 parameters in the schema, the baseline is 4, but the description adds minimal value by hinting at an ID requirement without details.
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 using the specified ID' clearly states the verb ('Update') and resource ('dashboard'), but it's vague about what aspects of a dashboard can be updated. It doesn't specify whether this updates settings, widgets, layout, or other properties, nor does it differentiate from sibling tools like 'update_dashboard_v1' or 'update_dashboards' (plural).
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. With siblings like 'update_dashboard_v1', 'update_dashboards', and 'create_dashboards', there's no indication of differences in scope, version, or use cases. It also lacks prerequisites, such as needing an existing dashboard ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.