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arch_reverse_probe

Identify target site's infrastructure using browser-accessible signals: fingerprint tech stack versions, infer middleware chain, probe ports, detect containerization, and match CVE vulnerabilities without SSH or database access.

Instructions

开源版架构逆向探测:通过浏览器可访问的信号逆向识别目标站点的基础架构。包括:1) 技术栈版本指纹(前端框架+版本号);2) 中间件链推断(Server 头、X-Powered-By、CSP、CORS);3) 端口旁路探测(同源常见端口 80/443/3000/8080/8000/5000 是否可达);4) 容器化信号检测(Docker/K8s 元数据泄露、.dockerenv 探测);5) CVE 初筛(基于识别到的版本号匹配已知 CVE)。不依赖 SSH/DB 权限,纯前端可访问信号。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes目标站点 URL(必填)
timeoutNo单个探测超时(毫秒)
probeCVENo基于识别到的版本号匹配 CVE
probePortsNo是否探测同源常见端口(80/443/3000/8080/8000/5000/9000)
customPortsNo自定义探测端口列表
probeDockerNo探测 Docker/K8s 容器化信号
Behavior4/5

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

With no annotations provided, the description carries full burden. It explains the tool probes the target via browser signals and enumerates the types of analysis. However, it does not explicitly state that the tool is non-destructive or read-only, nor does it disclose potential side effects like rate limiting or authorization needs. The description is informative but not fully exhaustive.

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 structured as a bulleted list with five items, front-loading the core purpose. It is detailed but each sentence is informative. While slightly lengthy, the complexity of the tool justifies the length. There is no redundancy.

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

Completeness3/5

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

The description covers inputs and high-level behavior well, but lacks any mention of the output format or response structure. Since there is no output schema, the description should provide guidance on what the tool returns (e.g., a JSON with results per probe). This gap makes it less complete for an agent to understand the full context.

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 baseline is 3. The description adds high-level context by listing the types of probes (CVE, ports, Docker) but does not provide parameter-specific details beyond what the schema already offers. For example, 'probePorts' is described in schema as '是否探测同源常见端口(80/443/3000/8080/8000/5000/9000)', which is sufficient.

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: '开源版架构逆向探测', and lists five specific areas it detects (tech stack versions, middleware chain, port probing, containerization signals, CVE matching). It distinguishes itself from sibling tools by focusing on infrastructure architecture detection via browser-accessible signals, which is distinct from API probing or security header analysis.

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 usage when you need to identify target infrastructure without SSH/DB access, stating '不依赖 SSH/DB 权限,纯前端可访问信号'. It provides clear context but does not explicitly state when not to use it or compare with specific sibling alternatives, though the distinct focus on architecture detection helps differentiate.

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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