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jamesbrink

MCP Server for Coroot

update_application_risks

Configure risk thresholds and monitoring parameters to identify potential issues before they impact users in Coroot applications.

Instructions

Update risk assessment configuration for an application.

Configures risk thresholds and monitoring parameters to better identify potential issues before they impact users.

Args: project_id: Project ID app_id: Application ID (format: namespace/kind/name) risks: Risk assessment configuration

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
app_idYes
risksYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler function that is registered via @mcp.tool() decorator and implements the core logic by calling the client implementation.
    @mcp.tool()
    async def update_application_risks(
        project_id: str,
        app_id: str,
        risks: dict[str, Any],
    ) -> dict[str, Any]:
        """Update risk assessment configuration for an application.
    
        Configures risk thresholds and monitoring parameters to better
        identify potential issues before they impact users.
    
        Args:
            project_id: Project ID
            app_id: Application ID (format: namespace/kind/name)
            risks: Risk assessment configuration
        """
        return await update_application_risks_impl(  # type: ignore[no-any-return]
            project_id, app_id, risks
        )
  • CorootClient method that performs the actual HTTP POST request to the Coroot API endpoint to update application risks.
    async def update_application_risks(
        self, project_id: str, app_id: str, risks: dict[str, Any]
    ) -> dict[str, Any]:
        """Update application risk assessment.
    
        Args:
            project_id: Project ID.
            app_id: Application ID (format: namespace/kind/name).
            risks: Risk assessment updates.
    
        Returns:
            Updated risk configuration.
        """
        # URL encode the app_id since it contains slashes
        from urllib.parse import quote
    
        encoded_app_id = quote(app_id, safe="")
    
        response = await self._request(
            "POST",
            f"/api/project/{project_id}/app/{encoded_app_id}/risks",
            json=risks,
        )
    
        # Handle different response types
        try:
            if response.headers.get("content-type", "").startswith("application/json"):
                data: dict[str, Any] = response.json()
                return data
            else:
                # If not JSON, return success with the provided risks
                return {
                    "app_id": app_id,
                    "risks": risks,
                    "status": "updated",
                }
        except Exception:
            # If parsing fails, return minimal success response
            return {"app_id": app_id, "status": "updated"}
  • Wrapper function decorated with error handler that calls the client method and formats the response.
    async def update_application_risks_impl(
        project_id: str,
        app_id: str,
        risks: dict[str, Any],
    ) -> dict[str, Any]:
        """Update application risk assessment."""
        result = await get_client().update_application_risks(project_id, app_id, risks)
        return {
            "success": True,
            "message": "Application risks updated successfully",
            "risks": result,
        }
  • FastMCP tool registration decorator applied to the handler function.
    @mcp.tool()
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 of behavioral disclosure. It states that the tool updates configuration, implying a mutation operation, but does not disclose critical behavioral traits such as required permissions, whether changes are reversible, rate limits, or what the output looks like. This is a significant gap for a mutation tool with zero annotation coverage.

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, with the core purpose stated first, followed by a brief explanation and a parameter list. It avoids unnecessary details, but the parameter section could be more integrated into the flow rather than a separate block. Overall, it is efficient with minimal waste.

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 complexity (mutation tool with nested objects), no annotations, and an output schema present (which reduces the need to describe return values), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and detailed usage guidelines. The presence of an output schema helps, but the description should do more to address the mutation nature and parameter specifics.

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?

Schema description coverage is 0%, so the schema provides no parameter details. The description adds some semantics by listing the parameters (project_id, app_id, risks) and specifying the app_id format (namespace/kind/name), which helps clarify usage. However, it does not fully compensate for the coverage gap, as it lacks details on the structure of 'risks' or validation rules, leaving parameters partially undocumented.

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 with a specific verb ('Update') and resource ('risk assessment configuration for an application'), and it distinguishes the tool by specifying what it configures (risk thresholds and monitoring parameters). However, it does not explicitly differentiate from sibling tools like 'update_ai_config' or 'update_inspection_config', which also update configurations for different aspects.

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 mentions configuring risk thresholds and monitoring parameters, but does not specify prerequisites, exclusions, or compare it to sibling tools such as 'get_risks_overview' or other update tools. This leaves the agent without clear usage context.

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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