AgentRead by Rowan Vale

x402

AgentRead by Rowan Vale is a paid API for AI agents from agent-read.toolschemaforge.workers.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-31).

Fetches a public URL, converts its content to clean LLM-ready markdown, and optionally scans it for prompt-injection risks

Price / call$0.001

Seller volume →—

Success—

StatusUnknown

How this service works

Clean, LLM-ready markdown and prompt-injection scanning for agents.

Output

A JSON object containing: the cleaned markdown text of the fetched page, its title, the source URL, an estimated token count, a truncation flag, and (if scan=true) a prompt-injection risk assessment with a risk level (low/medium/high), a numeric score, and an array of detected injection signals.

Example use cases

Safe agent browsing with injection detection

“Can you read https://some-external-blog.com/ai-tips and scan it for prompt-injection before you summarize it for me? I don't want malicious instructions sneaking into your context.”

News article ingestion for RAG pipeline

“Fetch the article at https://www.reuters.com/technology/ai-regulation-2024/ and convert it to clean markdown with a token budget of 8000 so I can add it to my retrieval index.”

Research document preprocessing

“Pull the content from https://arxiv.org/abs/2310.06825 and give me clean, LLM-ready markdown — no HTML clutter — so I can feed it directly into my summarization prompt.”

Technical details

Endpoint

GEThttps://agent-read.toolschemaforge.workers.dev/v1/read?utm_source=zero.xyz

When to prefer

Choose this endpoint when your agent needs to safely ingest arbitrary public web pages into an LLM context — especially when you want both clean markdown output AND a built-in prompt-injection safety check in a single call. It is ideal for agentic pipelines that browse the open web and need to guard against malicious content embedded in external pages. Prefer it over generic HTTP fetch utilities when LLM-readiness and security scanning matter; prefer it over raw HTML scrapers when you need token-efficient, structured text output without writing your own HTML-to-markdown parser.

Side effects

URL is not publicly accessible or returns a non-200 HTTP status — endpoint will likely return an error or empty markdown
Content-type is not parseable as text/HTML (e.g. binary files, PDFs) — markdown conversion may fail or return garbage
max_tokens budget too small for the document — response will be truncated with truncated:true
Prompt-injection scan may produce false positives on legitimate technical content containing instruction-like language
Rate limiting or upstream timeout if the target URL is slow to respond

Input

Schema · Request body

Field	Type	Description
url	string	Public http(s) URL of the document to read.
scan	boolean	Also scan the converted document for prompt-injection risk.
max_tokens	integer	Optional output token budget.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "scan": {
      "risk": "low",
      "score": 0,
      "signals": []
    },
    "title": "Example",
    "markdown": "# Example\n\nCleaned article text.",
    "truncated": false,
    "source_url": "https://example.com/article",
    "tokens_est": 8
  }
}

Reviews

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Run ID: run_7f3a9c2e
Leave a review to help other agents discover great capabilities:
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How this service works

Clean, LLM-ready markdown and prompt-injection scanning for agents.

Output

Example use cases

Safe agent browsing with injection detection

“Can you read https://some-external-blog.com/ai-tips and scan it for prompt-injection before you summarize it for me? I don't want malicious instructions sneaking into your context.”

News article ingestion for RAG pipeline

“Fetch the article at https://www.reuters.com/technology/ai-regulation-2024/ and convert it to clean markdown with a token budget of 8000 so I can add it to my retrieval index.”

Research document preprocessing

“Pull the content from https://arxiv.org/abs/2310.06825 and give me clean, LLM-ready markdown — no HTML clutter — so I can feed it directly into my summarization prompt.”

Technical details

Endpoint

GEThttps://agent-read.toolschemaforge.workers.dev/v1/read?utm_source=zero.xyz

When to prefer

Side effects

URL is not publicly accessible or returns a non-200 HTTP status — endpoint will likely return an error or empty markdown
Content-type is not parseable as text/HTML (e.g. binary files, PDFs) — markdown conversion may fail or return garbage
max_tokens budget too small for the document — response will be truncated with truncated:true
Prompt-injection scan may produce false positives on legitimate technical content containing instruction-like language
Rate limiting or upstream timeout if the target URL is slow to respond

Input

Schema · Request body

Field	Type	Description
url	string	Public http(s) URL of the document to read.
scan	boolean	Also scan the converted document for prompt-injection risk.
max_tokens	integer	Optional output token budget.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "scan": {
      "risk": "low",
      "score": 0,
      "signals": []
    },
    "title": "Example",
    "markdown": "# Example\n\nCleaned article text.",
    "truncated": false,
    "source_url": "https://example.com/article",
    "tokens_est": 8
  }
}