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configure_target

Set or update the REST chat endpoint, authentication, and request/response mapping for an AI red-teaming engagement.

Instructions

Configure (or replace) the REST chat target for an engagement.

    `target.request_template` is the JSON body sent to the endpoint, with the
    literal token `target.prompt_placeholder` (default "{{PROMPT}}") substituted
    with the outgoing prompt text anywhere it appears. `target.response_text_path`
    is a dotted/indexed path used to extract the reply text from the JSON response
    (e.g. "choices.0.message.content").
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
engagement_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
errorNo
successYes
Behavior4/5

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

The description discloses key behavioral traits: request_template substitution with prompt_placeholder, and response_text_path extraction. With no annotations, it carries the burden well, though it could mention that it replaces the existing target configuration.

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 relatively concise for the complexity, using a brief paragraph. It is front-loaded with the main purpose and expands on key parameters. Every sentence adds value, though could be slightly more structured.

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 and the presence of an output schema, the description covers the core configuration aspects. It explains the template substitution and response extraction adequately. Absence of return value explanation is mitigated by the output schema.

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?

Schema description coverage is 0% at the top level, but the description adds significant meaning: it explains the roles of request_template, prompt_placeholder, and response_text_path in detail, compensating for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Configure (or replace) the REST chat target for an engagement.' It uses specific verbs and resource, and distinguishes from sibling tools like get_target and validate_target by focusing on configuration.

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 explains the parameters but does not explicitly state when to use this tool versus alternatives like get_target or validate_target. It lacks prerequisites or context for usage, e.g., requiring an existing engagement.

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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