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jamesbrink

MCP Server for Coroot

get_application_rca

Identify root causes of application issues, including incidents and performance degradation, using AI-powered analysis.

Instructions

Get AI-powered root cause analysis for application issues.

Analyzes application problems and provides insights into the root causes of incidents, performance degradation, or failures.

Args: project_id: Project ID app_id: Application ID (format: namespace/kind/name)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
app_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, and the description lacks behavioral details such as prerequisites (e.g., AI model availability), side effects, or output format hints beyond 'provides insights'.

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 brief and front-loaded with the key action. However, the 'Args' section is somewhat redundant and could be integrated into the sentence.

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

Completeness3/5

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

The description covers the basic purpose but lacks detail on what the analysis output contains (though an output schema exists). It minimally addresses the tool's complexity.

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 adds format info for 'app_id' (namespace/kind/name) and repeats parameter names, but 0% schema coverage means it should do more; 'project_id' is vaguely described as 'Project ID'.

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

Purpose5/5

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

The description clearly states the tool retrieves AI-powered root cause analysis for application issues, distinguishing it from sibling tools like 'get_application' and 'get_application_logs'.

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 on when to use this tool vs alternatives (e.g., when to prefer logs over RCA). The description is purely functional.

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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