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get_ccn_freshness

Check the live CCN news pipeline health—article count, newest slug and age, IndexNow status, and sitemap URL count—to verify feed freshness before paying for per-article divergence data.

Instructions

[FREE] Read the CCN (Crypto-Currency Network) live news pipeline health: article count, newest slug, minutes since the newest article, IndexNow status, and the sitemap URL count, so you can tell whether the feed is fresh before you pay for anything.

For per-article freshness and post-publication divergence, agents pay $0.01 USDC on Base L2 via x402: POST https://agentworld.me/api/ccn/freshness/divergence with body {"slugs": [...]}.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_ccn_freshness"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavior burden. It usefully discloses that the call is free, lists the health metrics returned, and clearly marks the paid alternative, but it does not cover authentication, rate limits, error behavior, or response format details. That is adequate for a simple zero-parameter read, but incomplete for full behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the free read and its returned metrics, then uses a second short paragraph only for the relevant paid alternative. Every sentence supports either selecting the tool or understanding the cost boundary, with no wasted wording.

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 parameterless health-check tool with no output schema, the description supplies the key returned fields and the important cost distinction from the paid per-article endpoint. It is largely complete, though it could say more about the response shape or any access constraints.

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?

The input schema has zero parameters, so there is no parameter meaning for the description to add. The baseline for a parameterless tool is 4, and nothing in the description confuses the no-argument nature of the call.

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 states a specific read operation on the CCN live news pipeline health and enumerates the exact metrics returned: article count, newest slug, minutes since newest article, IndexNow status, and sitemap URL count. It also distinguishes this free aggregate health check from the paid per-article freshness/divergence endpoint, so an agent can identify its purpose without opening the schema.

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

Usage Guidelines5/5

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

It explicitly says to use this tool to tell whether the feed is fresh before paying for anything, which gives a clear triggering condition. It also names the paid alternative, including the endpoint, price, and purpose, so the agent knows when to use the paid per-article divergence call instead of this free aggregate check.

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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