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jamesbrink

MCP Server for Coroot

list_inspections

Retrieve all available inspection types and configurations for a Coroot project, including CPU, memory, SLO, and health checks.

Instructions

List all available inspections for a project.

Returns a list of all inspection types and their configurations including CPU, memory, SLO, and other health checks.

Args: project_id: Project ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler that fetches inspections using the Coroot client and returns formatted response.
    async def list_inspections_impl(project_id: str) -> dict[str, Any]:
        """List all available inspections."""
        inspections = await get_client().list_inspections(project_id)
        return {
            "success": True,
            "inspections": inspections,
        }
  • MCP tool registration via @mcp.tool() decorator with docstring defining the tool schema (inputs/outputs).
    @mcp.tool()
    async def list_inspections(project_id: str) -> dict[str, Any]:
        """List all available inspections for a project.
    
        Returns a list of all inspection types and their configurations
        including CPU, memory, SLO, and other health checks.
    
        Args:
            project_id: Project ID
        """
        return await list_inspections_impl(project_id)  # type: ignore[no-any-return]
  • CorootClient helper method that performs the HTTP request to retrieve inspections from the Coroot API.
    async def list_inspections(self, project_id: str) -> dict[str, Any]:
        """List all available inspections for a project.
    
        Args:
            project_id: Project ID.
    
        Returns:
            Dictionary of inspection configurations.
        """
        response = await self._request("GET", f"/api/project/{project_id}/inspections")
        data: dict[str, Any] = response.json()
        return data
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions returning a list with configurations including CPU, memory, SLO, and health checks, which adds some behavioral context. However, it lacks details on permissions, rate limits, pagination, or error handling. For a read operation with no annotations, 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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by return details and parameter explanation. There's no wasted text, but the structure could be slightly improved by integrating the 'Args' section more seamlessly. Overall, it's efficient and easy to parse.

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?

Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema, the description is somewhat complete. It covers purpose and parameter semantics adequately, but lacks usage guidelines and sufficient behavioral transparency. With no annotations and an output schema, it should do more to explain when and how to use the tool effectively.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'project_id: Project ID', which clarifies the parameter's purpose beyond the schema's generic 'Project Id' title. However, it doesn't provide format examples or constraints, leaving some ambiguity. With 0% coverage and one parameter, the description does a good job but could be more detailed.

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 tool's purpose: 'List all available inspections for a project' with specific verb ('List') and resource ('inspections'), and distinguishes it from siblings like 'get_inspection_config' by focusing on listing all types rather than configuring or getting a specific one. However, it doesn't explicitly differentiate from all siblings, such as 'get_application' or 'get_nodes_overview', which also list resources.

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. It doesn't mention prerequisites, exclusions, or compare to sibling tools like 'get_inspection_config' for specific configurations or 'list_projects' for broader context. Usage is implied by the action 'list all available inspections', but no explicit when/when-not instructions are given.

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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