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rnadjqaim
by rnadjqaim

run_red_team

Run safe red-team packs against authorized ML API endpoints to test security. Score responses and generate evidence for compliance frameworks.

Instructions

Run a safe red-team pack against an authorized ML API endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_urlYes
packNobaseline_safe
methodNoPOST
timeout_secondsNo
delay_secondsNo
max_casesNo
dry_runNo
headersNo
bearer_tokenNo
input_fieldNoinput
Behavior2/5

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

No annotations provided, so the description carries full burden. It declares the pack is 'safe' but does not disclose actual behaviors: whether it mutates state, requires authorization, has rate limits, or what happens if a vulnerability is found. The term 'red-team' implies adversarial testing, but consequences are unstated.

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?

While the description is concise at one sentence, it is severely under-specified for a tool with 10 parameters. Valuable information is sacrificed for brevity. The sentence lacks structure and does not front-load key behavioral details.

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

Completeness1/5

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

Given the tool's complexity (10 parameters, no output schema, no annotations), the description is grossly incomplete. It omits what a pack is, how method/timeout affect execution, the role of dry_run, and expected output. The agent cannot safely or effectively invoke this tool with only this description.

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

Parameters1/5

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

Schema description coverage is 0%, yet the description adds zero information about any of the 10 parameters (e.g., 'pack', 'dry_run', 'bearer_token'). The description fails to compensate for the missing schema descriptions, leaving agents unable to understand parameter purposes or constraints.

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 it runs a safe red-team pack against an authorized ML API endpoint. It uses specific verbs and resources, distinguishing it from sibling tools like 'run_ai_api_pentest' and 'evaluate_text'. The qualifiers 'safe' and 'authorized' set appropriate scope.

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?

No guidance on when to use this tool vs alternatives. It does not mention prerequisites, when not to use, or how to select among sibling tools like 'list_attack_packs' or 'run_ai_api_pentest'. The description lacks context for decision-making.

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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