AgentDiet JSON Repair & Web Distillation Endpoint

x402

AgentDiet JSON Repair & Web Distillation Endpoint is a paid API for AI agents from shopify-spy-72343955726.us-central1.run.app, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-14).

Fetches and distills web content into clean, agent-ready markdown with token compression metrics, suitable for downstream AI processing.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

15-App Autonomous Business-to-Agent (B2A) API Hub & MCP Suite. Supports Web Distillation, On-Chain Risk, DEX Token Intelligence, B2B Lead Enrichment, Domain OSINT, Email Verification, SEC Filings, GitHub Audits, Prompt Firewall, and native HTTP 402 (x402 Base USDC).

Output

Returns a JSON object containing distilled markdown content with a title and mode field, plus an ROI proof block showing raw token count, distilled token count, tokens saved, compression ratio percentage, and ROI multiplier — giving the agent quantified evidence of how much context was saved.

Example use cases

Compress docs for agent context

“Take this documentation page at https://stripe.com/docs/payments and distill it into compact markdown — I want to see how many tokens it saves compared to the raw version.”

Extract signal from noisy webpage

“There's a lot of noise on https://techcrunch.com/2024/05/01/some-article — can you distill just the meaningful content into clean agent-ready markdown and tell me the compression ratio?”

Repair and clean malformed JSON

“I have a messy JSON response from a scraper at https://mysite.com/data — can you run it through the JSON repair endpoint and give me back something clean and parseable?”

Technical details

Endpoint

GEThttps://shopify-spy-72343955726.us-central1.run.app/v1/json-repair?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to fetch external web content and compress it into token-efficient markdown before passing it to an LLM — especially when token cost is a concern. It is distinct from generic scrapers because it returns structured compression metrics (ROI multiplier, tokens saved) alongside the distilled content, letting agents make informed decisions about context budgets. Prefer this over raw fetch+parse pipelines when working with documentation pages, long-form articles, or noisy HTML that needs cleanup before agent consumption.

Side effects

Target URL is unreachable or returns non-200 status — endpoint may return an error status
Content is already minimal with low compression opportunity — ROI multiplier close to 1x
Malformed or unparseable source content — may return empty or partial markdown
Rate limiting or payment failure via x402/USDC — 402 response if payment not attached
Very large pages may time out on Google Cloud Run infrastructure

Output

Schema · Response

{
  "type": "json",
  "example": {
    "data": {
      "mode": "markdown",
      "title": "Example Documentation",
      "content": "# Example Documentation\nClean agent-ready markdown..."
    },
    "status": "ok",
    "roi_proof": {
      "raw_tokens": 14200,
      "tokens_saved": 13520,
      "roi_multiplier": 67.6,
      "distilled_tokens": 680,
      "compression_ratio_pct": 95.2
    }
  }
}

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