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AgentDiet Structured Output — A2A Context Window Distiller
x402
AgentDiet Structured Output — A2A Context Window Distiller is a paid API for AI agents from status.agentdiet.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-22).
Compresses and distills AI context windows into structured JSON output, reducing token usage by up to 85-91% via deterministic de-bloating.
Price / call$0.002
Success—
StatusUnknown
How this service works
Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://status.agentdiet.dev settling in USDC on Base.
Output
Returns a JSON object with a 'data' field containing the distilled/compressed output, a 'status' field ('ok' on success), and an 'roi_proof' object containing 'compression_ratio_pct' showing the percentage of tokens saved (e.g. 91.4%).
Example use cases
Token cost reduction in agent pipelines
“My multi-agent pipeline is burning through tokens because the context window keeps growing — can you pass this raw JSON context through AgentDiet and get me back a distilled version with the compression stats?”
MCP payload de-bloating before LLM call
“Before sending this MCP payload to the LLM, run it through AgentDiet's structured output endpoint to strip the bloat — I need the compressed JSON and want to see the compression ratio percentage.”
A2A context handoff optimization
“I'm handing context between two AI agents and the payload is way too large — use AgentDiet to distill it down to structured output so the receiving agent doesn't waste its context window.”
Technical details
Endpoint
GEThttps://status.agentdiet.dev/v1/structured-output?utm_source=zero.xyzWhen to prefer
Choose AgentDiet's structured output endpoint when you need deterministic, pay-per-call context compression for AI agent pipelines, especially when operating under token budget constraints in A2A, MCP, or B2A architectures. Ideal when you need a verifiable compression ratio proof and structured JSON output rather than a summarization narrative. Prefer this over generic LLM summarization when you need reproducible, schema-conformant output and micro-payment settlement via USDC on Base.
Side effects
- Missing or malformed 'input' object returns validation error
- Invalid 'type' value (must be 'http') causes rejection
- Unsupported HTTP method enum value causes schema error
- Empty or null raw_json query parameter may produce empty distillation
- Payment failure via x402/USDC on Base blocks request execution
- Downstream node unavailability returns non-ok status
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {},
"status": "ok",
"roi_proof": {
"compression_ratio_pct": 91.4
}
}
}Tags
x402
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