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Evaluate Public AI Web Readiness — Scan + Verified Evidence in One Call

evaluate_ai_web_readiness

FREE ONE-CALL EVALUATION: run the existing bounded public readiness scan, retrieve the matching persisted normalized evidence report, verify scan ID + hostname, then return observed findings and next actions in this one response. Unknown evidence is not a successful observation. Never charges or changes a website.

Input Schema

NameRequiredDescriptionDefault
domainYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description must carry the full behavioral burden and does so well: it declares the call is free, never charges or mutates a website, retrieves persisted (idempotent-style) evidence, and validates scan ID + hostname. It stops short of stating auth requirements, latency, or rate limits, but the safety/side-effect profile is unusually well disclosed.

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?

Front-loaded with the core benefit ('FREE ONE-CALL EVALUATION') followed by the pipeline steps and a constraint. It is dense but each clause adds meaning; no filler phrases.

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?

With no output schema and no annotations, the description explains the return at a meaningful level ('observed findings and next actions') and states the operation's side-effect safety. The main gap is the unexplained 'domain' parameter, which prevents a full 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single 'domain' parameter has 0% schema description coverage, so the description must compensate for the format, validity rules, and hostname relationship. It mentions 'hostname' verification but never explains what 'domain' should contain, leaving the parameter meaning entirely to inference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear composite verb sequence: run the bounded readiness scan, retrieve the matching persisted normalized evidence report, verify scan ID + hostname, and return findings. The 'ONE-CALL EVALUATION' framing makes it distinguishable from the sibling scan_ai_web_readiness + get_normalized_report two-step, though the siblings are not named explicitly.

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?

'FREE ONE-CALL EVALUATION' and 'Never charges or changes a website' imply it is the convenience alternative to multi-call flows, and 'Unknown evidence is not a successful observation' sets an interpretation rule. However, there is no explicit when-to-use vs when-not guidance or pointer to the sibling tools it wraps.

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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