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dual_chain_explore

Validates AI-generated code by running dual parallel chains: functional browser exploration and technical data flow tracing, then cross-references results to detect issues and auto-fix.

Instructions

双链路并行探索:链路① Browser Agent 在真实浏览器中做黑客式功能探索(发现→正向→对抗→闭环),链路② Trace Agent 追踪全栈数据流(前端→API→后端→数据库),交叉验证后输出多维判定(真通过/假通过/渲染问题/数据问题)并自动修复。两条链路独立并行,结果交叉对比,打破 AI 代码「自己验证自己」的闭环。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainsNo要执行的链路:'functional' 功能链路, 'technical' 技术链路。默认双链路并行
phasesNo要执行的阶段。默认 'all' 执行全部
targetYes目标系统 URL
autoFixNo发现断裂后是否自动修复。默认 true
dbConfigNo数据库配置,用于链路② Phase4 快照对比
sessionIdNo浏览器会话 ID(可选,不传则自动创建)
writeToMemoryNo是否将发现写入记忆体系。默认 true
explorationModeNo探索模式:normal 保守(top3), aggressive 全端点, hacker 最大攻击面+创造性探测normal
expectedBehaviorNo预期行为描述,用于 Phantom Data 检测
Behavior4/5

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

The description discloses key behavioral traits: two independent parallel chains, cross-validation, auto-fix, and the goal to break self-verification. No annotations were provided, so the description carries the full burden, and it does so reasonably well.

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 front-loaded with the core concept and provides comprehensive detail in a single paragraph. It is concise given the complexity, though a structured list could improve readability.

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 and lack of output schema, the description adequately explains the tool's process and what it achieves. It could mention the output format, but the cross-validation and auto-fix behavior is well-explained.

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 coverage is 100% and the description does not add significant meaning beyond the schema. It provides context for the overall process but does not elaborate on individual parameters beyond what the schema already provides.

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 the tool's purpose: dual-chain parallel exploration with specific chains (functional and technical), cross-validation, and auto-fix. It distinguishes itself from sibling tools by describing a complex multi-agent system that breaks the self-verification loop.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (thorough validation that breaks self-verification) but does not explicitly state when not to use or list alternatives. Given the context of sibling tools, this is clear enough.

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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