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generate_custom_payload

Generate custom prompt-injection test payloads from a template and variable values to evaluate AI system defenses and security controls.

Instructions

基于模板生成自定义攻击载荷

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
templateYes载荷模板(支持变量:{{target}}, {{action}}, {{context}})
variablesYes模板变量值

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

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 the full behavioral burden, yet it discloses nothing about the generated output's form, whether the payload is persisted or executed, safety/authorization expectations, or rate limits. Only the generative nature implied by '生成' is communicated.

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?

A single compact sentence with the mechanism and outcome front-loaded and no wasted words. It is arguably over-brief for a tool with no annotations, but there is no filler or redundancy.

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?

For a generation tool with no annotations and no output schema, the definition is too thin: it never explains what is returned, whether the payload is stored, or the safety context for producing attack payloads. The 100% schema coverage carries the parameter side, but the descriptive side is materially incomplete.

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%, so the schema already documents both parameters, including the supported variable placeholders ({{target}}, {{action}}, {{context}}) and the nested variables object. The description adds no meaning beyond the schema, so the baseline 3 applies.

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 states a specific verb and resource ('基于模板生成自定义攻击载荷' – generate a custom attack payload from a template) and even names the mechanism (template-based). It is clearly distinguishable from retrieval siblings like search_payloads or get_payload_by_id, though it does not explicitly name them.

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?

There is no explicit when-to-use guidance, no statement of when to prefer generating a custom payload over fetching an existing one via search_payloads/get_payloads_by_category, and no prerequisites or exclusions. The distinction from sibling retrieval tools is left entirely to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.