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Enkrypt AI MCP Server

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add_custom_redteam_task

Create and execute custom red-teaming tasks for AI models using predefined configurations. Specify model details, system descriptions, and tools to test model behavior. Ensure model availability before initiating tasks.

Instructions

Add a custom use-case basedredteam task using a saved model. NOTE: Not compatible with audio and image modalities.

Args: model_saved_name: The saved name of the model to be used for the redteam task. model_version: The version of the model to be used for the redteam task. custom_redteam_model_config: The configuration for the customredteam task. Example usage: sample_redteam_model_config = { "test_name": redteam_test_name, "dataset_configuration": { #Ask user for all these details, do not fill it on your own (system_description, policy_description and tools) "system_description": "", # The system description of the model for the custom use-case. (Mandatory) "policy_description": "", # The policy which the model for the custom use-case should follow. (Optional) "tools": [ { "name": "web_search", # The name of the tool to be used for the custom use-case. (Optional) "description": "The tool web search is used to search the web for information related to finance." # The description of the tool to be used for the custom use-case. (Optional) } ], #The following are the default values for the custom use-case. Change them only if the user asks for a different test size. "max_prompts": 500, # The maximum number of prompts to be used for the custom use-case. "scenarios": 2, # The number of scenarios to be used for the custom use-case. "categories": 2, # The number of categories to be used for the custom use-case. "depth": 1, # The depth of the custom use-case. } "redteam_test_configurations": { #IMPORTANT: Before setting the redteam test config, ask the user which tests they would want to run and the sample percentage. Note: The custom test is mandatory. other 5 are optional. "bias_test": { "sample_percentage": 2, "attack_methods": {"basic": ["basic"]}, }, "cbrn_test": { "sample_percentage": 2, "attack_methods": {"basic": ["basic"]}, }, "insecure_code_test": { "sample_percentage": 2, "attack_methods": {"basic": ["basic"]}, }, "toxicity_test": { "sample_percentage": 2, "attack_methods": {"basic": ["basic"]}, }, "harmful_test": { "sample_percentage": 2, "attack_methods": {"basic": ["basic"]}, }, "custom_test": { "sample_percentage": 100, # The sample percentage for the custom use-case. Keep it at 100 unless the user asks for a different sample percentage. "attack_methods": {"basic": ["basic"]}, } }, }

    Befor calling this tool, ensure that the model name is availble. If not, save a new model then start the redteaming task.

Returns: A dictionary containing the response message and details of the added redteam task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
custom_redteam_model_configYes
model_saved_nameYes
model_versionYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a mutation tool (implied by 'Add'), includes important constraints (incompatibility with audio/image modalities), specifies prerequisites (check model availability), and outlines complex configuration requirements. It doesn't cover rate limits or error handling, but provides substantial operational context.

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 description is excessively long and poorly structured. While the initial purpose statement is clear, it's followed by a massive embedded example that dominates the text. The information is valuable but not front-loaded efficiently, making it difficult for an agent to quickly parse essential details. The length exceeds what's necessary for concise tool selection.

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 complexity (3 parameters with nested objects, 0% schema coverage, no output schema, no annotations), the description provides substantial context. It explains the tool's purpose, constraints, prerequisites, and detailed parameter semantics. The main gap is the lack of output description (returns 'a dictionary' without specifics), but otherwise it addresses the tool's operational needs reasonably well.

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?

With 0% schema description coverage, the description must fully compensate. It provides detailed semantic explanations for all three parameters: 'model_saved_name' and 'model_version' are clearly defined, and 'custom_redteam_model_config' receives extensive documentation with a comprehensive example structure, mandatory/optional fields, and usage instructions. This goes far beyond what the bare schema provides.

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: 'Add a custom use-case based redteam task using a saved model.' It specifies the verb ('Add') and resource ('custom use-case based redteam task'), and distinguishes it from siblings by mentioning 'custom' and incompatibility with audio/image modalities. However, it doesn't explicitly differentiate from 'add_redteam_task' or 'add_agent_redteam_task' among the siblings.

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 provides some usage context: it notes incompatibility with audio/image modalities and includes a prerequisite to ensure the model name is available before calling. However, it lacks explicit guidance on when to use this tool versus alternatives like 'add_redteam_task' or 'add_agent_redteam_task', and doesn't specify exclusions or detailed alternatives.

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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