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Detect a website's tech stack

detect_tech_stack
Read-onlyIdempotent

Fetch one web page and report the technologies behind it (CMS, ecommerce platform, analytics, CDN, web server, frameworks, payment processors, email provider) with a confidence and the evidence for each. Reads HTML, headers, cookies and DNS from one page load; it cannot see what only a running browser reveals.

Input Schema

NameRequiredDescriptionDefault
urlYesA domain or a full web address to analyze.
min_confidenceNoHide detections below this confidence, 0 to 100. Default 50.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, yet the description adds real value: the evidence sources it inspects (HTML, headers, cookies, DNS), that each detection comes with a confidence and supporting evidence, and the single-page-load limitation. It does not mention cost, rate limits, or behavior on an unreachable URL, which keeps it below a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and output shape, then the mechanics and the key limitation. Every clause carries information and nothing is redundant.

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

Completeness5/5

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

With no output schema, the description carries the burden of explaining returns and does so (technologies by category, each with confidence and evidence). Combined with the source list and the JS-rendering caveat, an agent has everything needed to decide to call it and interpret results.

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%, so both parameters are already documented including the min_confidence default of 50. The description only reinforces the meaning of confidence ('with a confidence and the evidence for each') and the 'one page load' scoping, adding no syntax or format detail beyond the schema — appropriate baseline of 3.

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?

States a concrete verb and resource ('Fetch one web page and report the technologies behind it') and enumerates the detection categories (CMS, ecommerce, analytics, CDN, web server, frameworks, payment processors, email provider), which clearly separates it from generic page-reading siblings like read_page or extract_page even though those are not named.

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?

Gives clear operating context ('Reads HTML, headers, cookies and DNS from one page load') and an explicit exclusion ('cannot see what only a running browser reveals'), which steers an agent away from using it for JS-rendered content. It does not directly name an alternative tool such as read_page/extract_page for that case, so it stops short of a full when/when-not/alternative map.

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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