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Scan a website for agent readiness

scan_website

Score any public website out of 100 for how well AI agents can use it: reach it, understand it, act on it (book, quote, buy), complete the task, act for a signed-in customer, trust its facts, and find the right location. Returns the score, a score per area, the most important finding in each area, and a link to the full report with every finding and the ordered fix plan. Takes 5 to 20 seconds.

Input Schema

NameRequiredDescriptionDefault
urlYesThe website to scan, for example acme.com or https://www.acme.com/
freshNoRescan even if the site was scanned in the last 30 minutes. Use after the owner changed something.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Description adds valuable context beyond annotations: return structure (overall score, per-area scores, top finding per area, report link), performance expectation (5-20 seconds), and scope constraint ('public website'). Annotations declare readOnlyHint=false and openWorldHint=true, which the description is consistent with. Minor gap: it doesn't explain the caching behavior that 'fresh' implies.

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 dense sentence plus a concise output sentence, front-loaded with the core purpose and score scale. Free of filler, though the long enumeration of scoring areas makes it slightly dense.

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?

Covers what it returns (compensating for no output schema) and the time cost, and the scope constraint is clear. A small gap remains around whether results are stored for retrieval via get_report, but overall an agent has what it needs to call it correctly.

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% with detailed parameter descriptions, including examples for url and the 'fresh' caching semantics. The description adds nothing beyond the schema regarding parameters, so baseline 3 applies.

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 specific verb (score) and resource (public website) with the exact output (out of 100) and the dimensions evaluated. Clearly distinguishes from siblings: this is the scanning action, while get_report retrieves an existing report and get_scoring_method explains criteria.

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

Usage Guidelines3/5

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

Implies when to use (to score a public website for agent readiness) and covers rescan behavior via the 'fresh' parameter semantics, but does not explicitly state when NOT to use it or point to siblings like get_report for existing results. Usage context is implicit rather than stated.

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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