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SignalHarness Prompt Instruction Conflict Detector
x402
SignalHarness Prompt Instruction Conflict Detector is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Analyzes a prompt or instruction set (as JSON) to detect conflicts, contradictions, or ambiguities between directives that could cause unpredictable agent behavior.
Price / call$0.01
Success—
StatusUnknown
How this service works
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Output
Returns an analysis object containing a list of conflict warnings, an analysis_json field with structured findings, and an evidence_scope label indicating the data source. The response includes a signed receipt with payment confirmation, execution metadata, and a SHA-256 hash of the result for auditability.
Example use cases
Pre-deployment system prompt audit
“Before I deploy this agent, can you analyze its instruction set for any conflicting rules? Here's the JSON: {"instructions": ["respond only in English", "always respond in the user's language", "keep answers under 50 words", "always give thorough explanations"]}”
Multi-agent directive conflict check
“I'm building a multi-agent pipeline and I want to make sure the orchestrator's instructions don't contradict the sub-agent's instructions — can you run a conflict detection on this combined instruction JSON I'll send you?”
Prompt safety validation before release
“Can you scan this prompt configuration JSON for any instruction conflicts that might cause the model to behave unpredictably in production? I want a list of warnings before we ship it.”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/prompt_instruction_conflict_detect/invokeWhen to prefer
Choose this endpoint when you need to programmatically validate that a prompt or instruction set for an LLM agent is internally consistent before deployment or at runtime. It is especially useful in agentic pipelines where conflicting directives could cause unpredictable behavior, infinite loops, or safety failures. Prefer it over manual review when operating at scale or when automated pre-flight checks are required.
Side effects
- Malformed or invalid JSON in request_json field returns an error
- Empty or too-short input (below minLength of 2) is rejected
- Input exceeding 65536 characters is truncated or rejected
- Ambiguous instructions may produce false-positive or false-negative conflict reports
- Service may not detect semantic conflicts that require deep domain knowledge
- Payment failure (x402) prevents execution and returns 402 status
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request_json | string |
Output
Schema · Response
{
"type": "json",
"example": {
"replay": false,
"result": {
"warnings": [
"Verify the caller-supplied data before relying on this result."
],
"service_id": "prompt_instruction_conflict_detect",
"analysis_json": "{\"example\":\"schema-valid caller-supplied data\"}",
"evidence_scope": "caller_supplied_data"
},
"status": "succeeded",
"receipt": {
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"usage": [],
"status": "succeeded",
"network": "eip155:8453",
"artifacts": [],
"endedAtMs": 0,
"latencyMs": 0,
"paymentId": "example-payment",
"receiptId": "example-receipt",
"requestId": "example-request",
"serviceId": "prompt_instruction_conflict_detect",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "10000",
"resultSha256": "11de2d35cbdea149b84900382222c1c169b0f097ea592c73afd677256d1f7cbf",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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