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Novarithm Agent Hub: trust and commerce checks

monitor_subscribe_1d

[PAID $0.02 USDC/call, x402, eip155:8453] Subscribe one agent to monitoring for 24 hours: an immediate first measurement plus one deterministic re-check, with history and regression alerts. Returns a sub_id and a token; read your state for free at /agents/monitor/status. Use it to test the service on one agent before committing to a longer window.

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": "monitor_subscribe_1d"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesPublic origin of the agent to monitor, e.g. https://api.example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations at all, the description carries the whole burden and does well: it discloses the paid x402 model ($0.02 USDC/call, eip155:8453), the exact deliverable cadence (one immediate measurement plus one deterministic re-check), the returned credentials (sub_id and token), and a free status endpoint. It omits failure/refund behavior and whether re-subscribing the same URL is idempotent.

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?

Three sentences, front-loaded with the price/payment context an agent needs before calling a paid tool, then the deliverable, then the trial-use guidance. Dense but each clause carries information; no filler.

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 paid subscription tool with no annotations and no output schema, the description covers cost, returned values, and the free status path, which is most of what an agent needs. Only edge-case behavior (expiry, re-subscription, failed measurements) is left unspecified.

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?

Only one parameter and schema coverage is 100%, so the schema already explains that `url` is the public origin of the agent to monitor. The description only adds the scoping notion of 'one agent' and nothing about URL validation or reachability requirements, so baseline 3 applies.

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 specific verb and resource plus an exact scope: 'Subscribe one agent to monitoring for 24 hours', and enumerates what the subscription includes (immediate measurement, one deterministic re-check, history, regression alerts). The closing phrase 'before committing to a longer window' implicitly carves it out from monitor_subscribe_7d and monitor_subscribe_30d, though it never names those siblings.

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 when-to-use guidance: trial on a single agent before buying a longer window, with free follow-up via /agents/monitor/status. It does not explicitly state when NOT to use it (e.g. for multi-agent or ongoing production monitoring), so the alternative selection is inferred rather than spelled out.

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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