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Datadog MCP Server

by datgfg

list_dashboards

Retrieve and filter Datadog dashboards by name or tags to access monitoring data and visualizations for observability analysis.

Instructions

Get list of dashboards from Datadog

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFilter dashboards by name
tagsNoFilter dashboards by tags
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states it 'gets' dashboards (implying a read operation) but doesn't mention pagination, rate limits, authentication requirements, or what the return format looks like. For a list tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple list operation and front-loads the essential information (get list of dashboards).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (list operation with filtering parameters), lack of annotations, and no output schema, the description is insufficiently complete. It doesn't explain what information is returned about each dashboard, how results are structured, or any limitations (like maximum results). For a tool that presumably returns multiple items, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description doesn't mention any parameters, but the input schema has 100% description coverage, with clear documentation for both 'name' (filter by name) and 'tags' (filter by tags). Since the schema does the heavy lifting, the baseline score of 3 is appropriate - the description adds no parameter semantics beyond what's already in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get list') and resource ('dashboards from Datadog'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_dashboard' or other list tools like 'list_incidents' or 'list_metrics', which would require more specific scope information to earn a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. There's no mention of when to choose 'list_dashboards' over 'get_dashboard' (which presumably retrieves a single dashboard), or how it relates to other list tools like 'list_incidents'. Without any usage context or exclusions, this is minimal guidance.

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

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