OMENZ agent tools

agent_ready

Score 0-100 for how well AI assistants and agents can find, read and use a business website, with prioritized plain-language fixes. Deterministic, no AI calls. By OMENZ. (MCP calls run in AYNE, the free playzone; production: GET https://www.omenz.org/api/tollbooth/v1/agent-ready, $0.10 via x402.)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "agent_ready"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	Public website URL

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations supplied, the description carries the full burden and does substantial work: it discloses determinism, absence of AI calls (so results are reproducible and cheap), the transport split between the free MCP playzone and the production HTTP endpoint, and the $0.10 x402 price. What it omits is failure behavior (invalid/unreachable URLs) and any rate or size limits.

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 core capability is front-loaded in the first sentence, with behavioral qualifiers compressed into short trailing clauses. The parenthetical about AYNE/production/x402 is dense but genuinely useful billing context, not padding.

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?

For a one-parameter tool with no output schema and no annotations, the description covers purpose, output shape, determinism, and cost/transport. It stops short of describing error cases or the structure of the returned fixes, which are the main remaining gaps.

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% and the single parameter `url` is already documented as a "Public website URL" in the schema. The description adds no format, scoping, or validation detail beyond that, so the baseline of 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), a specific resource (a business website's readiness for AI assistants/agents), the output shape (0-100 plus prioritized plain-language fixes), and the evidence basis (deterministic, no AI calls). The sibling catalog is a set of unrelated utility names, so there is no plausible ambiguity to disambiguate against.

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?

Usage is only implied: an agent can infer you call this to audit a public website before/after improving it. There is no explicit when-to-use, no when-not-to-use, and no named alternative within the toolset.

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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