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Brucedh

AWS‑IReveal‑MCP

networkinsights_start_analysis

Initiate Network Access Scope analysis to assess and document AWS network security configurations and permissions.

Instructions

Start a Network Access Scope analysis.

Parameters:
aws_region (str): AWS region - use 'us-east-1' if not specified.
scope_id (str): The NetworkInsightsAccessScopeId to analyze.
dry_run (bool): If True, checks permissions without starting.
tag_specifications (list): TagSpecification dicts for annotating the analysis.
client_token (str): Idempotency token for the request.

Returns:
str: JSON representation of the NetworkInsightsAccessScopeAnalysis object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aws_regionYes
scope_idYes
dry_runNo
tag_specificationsNo
client_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • This is the handler function for the 'networkinsights_start_analysis' tool. It uses the boto3 EC2 client to start a Network Insights Access Scope analysis, passing parameters like scope_id, dry_run, tags, and client_token. It returns the JSON of the created analysis object.
    @mcp.tool()
    async def networkinsights_start_analysis(
        aws_region: str,
        scope_id: str,
        dry_run: bool = False,
        tag_specifications: list[dict] = None,
        client_token: str = None
    ) -> str:
        """
        Start a Network Access Scope analysis.
    
        Parameters:
        aws_region (str): AWS region - use 'us-east-1' if not specified.
        scope_id (str): The NetworkInsightsAccessScopeId to analyze.
        dry_run (bool): If True, checks permissions without starting.
        tag_specifications (list): TagSpecification dicts for annotating the analysis.
        client_token (str): Idempotency token for the request.
    
        Returns:
        str: JSON representation of the NetworkInsightsAccessScopeAnalysis object.
        """
        client = boto3.client('ec2', region_name=aws_region)
        params = {'NetworkInsightsAccessScopeId': scope_id}
        if dry_run:
            params['DryRun'] = True
        if tag_specifications:
            params['TagSpecifications'] = [{
                'ResourceType': 'network-insights-access-scope-analysis',
                'Tags': tag_specifications
            }]
        if client_token:
            params['ClientToken'] = client_token
    
        response = client.start_network_insights_access_scope_analysis(**params)
        analysis = response.get('NetworkInsightsAccessScopeAnalysis', {})
        return json.dumps(analysis, indent=2, cls=DateTimeEncoder)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that the tool 'starts' an analysis and returns a JSON representation, but doesn't cover important aspects like whether this is a long-running operation, what permissions are required, potential costs, rate limits, or what happens to existing analyses. The dry_run parameter hint about permission checking is useful but insufficient.

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 well-structured and efficiently organized. It begins with the core purpose, then provides a clear parameter section with bullet-point explanations, and ends with return value information. Every sentence adds value with no redundant information.

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

Completeness4/5

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

Given the tool's complexity (5 parameters, no annotations, but with output schema), the description does well. The parameter explanations are thorough, and the return value is documented. However, for a tool that 'starts' an analysis (implying potential mutation and operational impact), more behavioral context about what 'starting' entails would improve completeness.

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

Parameters5/5

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

The description provides excellent parameter semantics despite 0% schema description coverage. Each parameter is clearly explained with purpose and usage guidance: default values ('use us-east-1 if not specified'), idempotency context for client_token, permission checking for dry_run, and annotation purpose for tag_specifications. This fully compensates for the lack of schema descriptions.

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 action ('Start a Network Access Scope analysis') with the specific resource type, which is helpful. However, it doesn't differentiate this tool from sibling tools like 'networkinsights_list_analyses' or 'networkinsights_get_findings', which would require more specificity about what makes this 'start' operation unique.

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 like 'networkinsights_list_analyses' or 'networkinsights_get_findings'. It mentions a 'dry_run' parameter for permission checking, but doesn't explain broader usage context, prerequisites, or typical workflows for starting an analysis.

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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