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by rad-security
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TypeScript
Remote

get_container_llm_analysis

Analyze container process trees using LLM to identify security risks in Kubernetes environments.

Instructions

Get LLM analysis of a container's process tree

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "container_id": "<container_id>"
    },
    "name": "get_container_llm_analysis"
  }
}

Input Schema

NameRequiredDescriptionDefault
container_idYesContainer ID to get LLM analysis for

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
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. While 'Get' implies a read operation, it doesn't disclose behavioral traits like authentication requirements, rate limits, what 'LLM analysis' entails, response format, or potential side effects. The description is minimal and lacks necessary context for safe invocation.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete for a tool that presumably returns complex LLM analysis results. It doesn't explain what 'LLM analysis' includes, the format of the output, or any behavioral considerations. For a tool with potential complexity, this minimal description leaves significant gaps.

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 100% (the single parameter 'container_id' is documented in the schema), so the baseline is 3. The description doesn't add any meaningful parameter semantics beyond what's already in the schema—it mentions 'container' but provides no additional context about format, constraints, or examples.

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 ('Get LLM analysis') and the target resource ('container's process tree'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_container_details' or 'get_containers_process_trees', which might offer related but different functionality.

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. With multiple sibling tools related to containers (e.g., 'get_container_details', 'get_containers_process_trees'), there's no indication of context, prerequisites, or exclusions for this specific LLM analysis tool.

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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