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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

update_slo_correction

Modify existing SLO corrections in Datadog to adjust monitoring thresholds and maintain accurate service level tracking.

Instructions

Update the specified SLO correction object.

Tool call template

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_slo_correction"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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 'update' which implies a mutation, but doesn't disclose behavioral traits such as 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.

Conciseness4/5

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

The description is a single sentence with no wasted words, making it appropriately concise. However, it's front-loaded but under-specified, lacking necessary details for a mutation tool. It earns points for brevity but loses some for not being sufficiently informative.

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 complexity of a mutation tool with no annotations, no output schema, and 0 parameters, the description is incomplete. It doesn't explain what an 'SLO correction object' entails, how to specify it, what fields can be updated, or the expected outcome. For a tool in a context with many siblings, more context is needed.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so the schema already fully documents the lack of parameters. The description doesn't add parameter details beyond this, but with 0 parameters, the baseline is high as there's nothing to compensate for. It implicitly suggests an SLO correction object must be specified, but this isn't detailed.

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

Purpose3/5

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

The description 'Update the specified SLO correction object' clearly states the action (update) and resource (SLO correction object), but it's vague about what aspects can be updated and lacks differentiation from sibling tools like 'update_slo' or 'create_slo_corrections'. It provides a basic purpose but doesn't specify the scope or fields involved.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing SLO correction), exclusions, or comparisons to siblings like 'create_slo_corrections' or 'delete_slo_correction'. Usage is implied but not explicitly stated.

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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