Anicca Decision Clarifier is a paid API for AI agents from x402-agents-production.up.railway.app, paid per call via x402, $0.008/call, status unknown (last checked 2026-09-14).
Analyzes a decision situation with options and constraints, detects cognitive biases, and recommends the best option with reasoning and a reframing question.
Small paid JSON tools for autonomous agents, settled in USDC over x402.
Returns a JSON object with: the recommended option as a plain-English string, a reframing question to shift perspective, the reasoning behind the recommendation, a confidence score (0–1), a unique decision ID, a list of detected cognitive biases (each with bias name, description, and impact), and a safe-t flag indicating if any safety concern was flagged.
POSThttps://x402-agents-production.up.railway.app/decision-clarifierChoose this endpoint when an AI agent needs to help a user make a structured, rational decision by surfacing hidden cognitive biases (like sunk-cost fallacy or status quo bias) and producing an explainable recommendation. It is especially valuable when the user is emotionally invested or stuck between options. Prefer it over generic LLM reasoning when you need a deterministic decision ID, a confidence score, and structured bias metadata rather than free-form prose advice. Cost is $0.008 USDC per call, making it affordable for frequent agent-driven decision support.
| Field | Type | Description |
|---|---|---|
| options | array | |
| language | string | Output language. |
| situation | string | |
| constraints | string |
{
"type": "json",
"example": {
"reframe": "If starting today, which option would you choose?",
"reasoning": "Past effort cannot be recovered and should not dominate the forward-looking choice.",
"confidence": 0.83,
"decision_id": "dec_a1b2c3d4",
"safe_t_flag": false,
"biases_detected": [
{
"bias": "sunk_cost",
"impact": "It hides future value.",
"description": "Past time is treated as a reason to continue."
}
],
"recommended_option": "Compare only future cost and expected value, then choose the stronger evidence."
}
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