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Novarithm Agent Hub: trust and commerce checks

by com.novarithm.www
OverviewDiscussionsAdmin

clone_blueprint

[PAID $49 USDC/call, x402, eip155:8453] Architecture plan + installation checklist for one AI-run business: clone=agency (AI sales-agent agency), trading-house (AI B2B trading house) or api-store (API store for AI agents). Components, data flows, build phases, done-when checklist, go-live checks. No source code, no revenue promise. Unknown clone = not charged.

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": {
      "clone": "<clone>"
    },
    "name": "clone_blueprint"
  }
}

Input Schema

NameRequiredDescriptionDefault
cloneYesagency | trading-house | api-store

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses cost ($49 USDC per call), the payment rail (x402, eip155:8453), what the deliverable contains (components, data flows, build phases, done-when checklist, go-live checks), what it explicitly does not contain (no source code, no revenue promise), and the no-charge guarantee on an unrecognized clone. The remaining gap is delivery mechanics — nothing about response format (JSON vs. markdown document) or latency.

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 block with the price/rail front-loaded in brackets, followed immediately by the deliverable and the enumeration of options. Every clause carries information — inclusions, exclusions, and billing edge case — with no filler. It is slightly over-packed (price, protocol, catalog, scope, and billing rule in one paragraph), which hurts skimmability more than length.

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 annotations and no output schema, the description covers cost, input domain, output contents, and explicit scope limits — enough for an agent to decide and call correctly. The only material omission is the shape of the response (structured document vs. prose), which matters because no output schema exists to fill that gap.

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

Parameters4/5

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

Schema coverage is 100% and the single parameter is already documented as 'agency | trading-house | api-store', so the baseline is 3. The description earns the bump by glossing each value ('agency (AI sales-agent agency), trading-house (AI B2B trading house) or api-store (API store for AI agents)') and by stating the error behavior for an invalid value, which the schema does not capture.

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 names the exact deliverable ('Architecture plan + installation checklist for one AI-run business') and enumerates the three supported subjects, so there is no ambiguity about what is returned. It also pre-empts a likely misread of the name 'clone' by stating 'No source code', confirming this is a planning document, not an implementation. No sibling tool overlaps, so differentiation is trivially achieved.

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 it should call this when it wants a build plan for one of the three named AI-business models. There is no explicit 'use this when…' framing, no statement of prerequisites, and no comparison to any alternative (there is no close sibling, so this is a low-cost omission). 'Unknown clone = not charged' hints at input validation but is behavioral, not usage, guidance.

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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