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detect_technologies

Analyzes a website to detect its underlying technologies, frameworks, and libraries.

Instructions

Detect technologies, frameworks, and libraries used by a website.

Args: url: Target URL user_agent: Optional custom User-Agent string

Example: detect_technologies("https://example.com") detect_technologies("https://example.com", "Mozilla/5.0... bug-bounty")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
user_agentNo
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only mentions detecting technologies and an optional user agent, but omits critical details like that the tool likely fetches the website, may be noisy, respects robots.txt or not, or is read-only. The example hints at custom user agents for bug bounty but doesn't explain implications.

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 short and front-loaded with the purpose. It lists parameters and an example without extraneous text. However, it could benefit from a structured format separating purpose, usage, and output, though it remains efficient.

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?

Given the absence of output schema and annotations, and the likelihood that this tool performs a network scan, the description is incomplete. It does not explain what detection entails (e.g., parsing HTML, headers, or JS), how results are returned, or whether the tool is passive or active. The example lacks output illustration.

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 0%, so the description must compensate. It provides basic descriptions: url is 'Target URL' and user_agent is 'Optional custom User-Agent string'. This adds minimal meaning beyond the schema's type information. The example shows usage but no parameter details beyond placeholders.

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 detects technologies, frameworks, and libraries used by a website. This specific verb+resource distinguishes it from sibling tools like whois_info or dns_records, which deal with domain registration or DNS data.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention that it is ideal for reconnaissance or that it should be avoided for simple domain queries. The agent gets no context for tool selection.

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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