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Threat Modeling MCP Server

Official
by awslabs

get_trust_boundary_analysis_plan

Generate a structured trust boundary analysis plan to identify security concerns, using AI prompts and AWS documentation for validation.

Instructions

Get a comprehensive trust boundary analysis plan.

This tool returns a detailed plan for analyzing trust boundaries for security concerns using AI-powered analysis with AWS documentation validation.

Args: ctx: MCP context for logging and error handling

Returns: A markdown-formatted trust boundary analysis plan with prompts for LLM analysis

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses that the plan is AI-powered, validated against AWS documentation, and returns markdown with prompts for LLM analysis, which is useful beyond a simple 'returns plan' statement. It doesn't explicitly state side effects, but as a getter, the behavior is largely transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

The first sentence is a near-tautology of the tool name, repeating 'get a comprehensive trust boundary analysis plan.' The 'Args' section introduces a non-schema parameter that adds confusion, and the structure is somewhat padded.

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 tool is simple with no parameters and has an output schema, so return values are covered. However, given the large list of sibling plan-related tools, the description lacks enough context to help an agent choose between this and similar plans like get_trust_boundary_detection_plan or get_architecture_analysis_plan.

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 tool has zero parameters and the schema is empty, so the baseline is 4. The description mentions a 'ctx' arg for logging, which is not in the schema and may confuse, but it doesn't need to describe actual parameters. The extra mention is not meaningful but doesn't undermine the baseline.

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 returns a detailed plan for analyzing trust boundaries, specifying the resource and purpose. It doesn't explicitly differentiate from sibling tools like get_trust_boundary_detection_plan or get_architecture_analysis_plan, but the focus on 'analysis' and 'security concerns' provides enough clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a trust boundary analysis plan is needed, but it provides no explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned, so the context is only lightly implied.

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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