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AgentDiet Context Diet – Web URL Distiller
AgentDiet Context Diet – Web URL Distiller is a paid API for AI agents from preflight.agentdiet.dev, paid per call via MPP, $0.001/call, status unknown (last checked 2026-10-21).
Fetches and compresses a webpage (or raw HTML) into compact, agent-ready tokens using BM25-ranked budget control and multiple distillation modes
Price / call$0.001
Success—
StatusUnknown
How this service works
Distill a URL or raw HTML payload with BM25 budget control (Live x402 v2, IETF MPP & MCP endpoint at https://preflight.agentdiet.dev/v1/context-diet)
Output
Returns a 'data' object containing the distilled content (Markdown, structured JSON, skeleton, or BM25 excerpt depending on mode), plus an roi_proof block showing raw token count, distilled token count, tokens saved, compression ratio percentage, estimated LLM cost saved in USD, and ROI multiplier. Also includes cache status (HIT/MISS) and billing details.
Example use cases
Compress docs page for agent context
“Grab the OpenAI API reference at https://platform.openai.com/docs/api-reference and distill it into structured JSON tables so I can pass only the relevant parts to my agent without blowing my context window.”
Budget-capped research on competitor pricing
“Fetch https://vercel.com/pricing and give me a BM25-focused excerpt under 300 tokens that highlights the parts about 'team plan pricing' — I only want the most relevant content.”
Skeleton outline of a long article
“Distill https://en.wikipedia.org/wiki/Large_language_model into a skeleton outline so I can see the document structure and headings without reading the whole thing.”
Technical details
Endpoint
GEThttps://preflight.agentdiet.dev/v1/context-diet?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your agent needs to read webpage content but must stay within a token budget — especially when passing web content into an LLM context window where cost and size matter. Prefer it over raw HTTP fetching when you need markdown conversion, structured extraction, or BM25-ranked relevance filtering. Ideal when LLM token costs are a concern and you want quantified proof of compression savings.
Side effects
- Invalid or unreachable URL returns fetch error
- max_tokens below minimum of 20 returns validation error
- mode=budget without a query returns degraded results
- Raw HTML too large may exceed processing limits
- Payment failure (x402) if agent lacks sufficient USDC balance
- Cache MISS on first call may increase latency
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| urlrequired | string | Target webpage URL to fetch and distill (or builtin://stripe-docs) |
| html | string | Optional raw HTML string to distill directly without fetching |
| mode | string | Distillation mode |
| query | string | BM25 focus query when mode=budget |
| max_tokens | integer | Strict token budget ceiling when mode=budget |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| datarequired | object | Distilled Markdown, structured JSON tables/metadata, skeleton outline, or BM25 budget excerpt. |
| cache | object | |
| statusrequired | string | Execution status ('ok') |
| billing | object | |
| roi_proofrequired | object |
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