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AUN Memory Health Check
x402
AUN Memory Health Check is a paid API for AI agents from a-upgradenet.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-22).
Audits a batch of AI agent memories for issues like secrets, contradictions, duplicates, and vague entries, then returns a graded cleanup plan with redacted/cleaned versions.
Price / call$0.05
Success—
StatusUnknown
How this service works
Memory Health Check: scans an AI agent's long-term memory for leaked secrets, personal data, duplicates, contradictions and vague entries; returns a 0-100 score, issues and a cleaned memory list ready to apply.
Output
Returns a letter grade (e.g. 'C') and numeric score (0-100) for the memory batch, a list of specific issues (type, severity, affected memory IDs, recommended action), a summary count of issue categories (vague, secrets, duplicates, personal_data, contradictions), a structured cleanup plan listing which memory IDs to delete, redact, or rewrite, and the cleaned/redacted versions of affected memories.
Example use cases
Pre-deployment memory security scan
“Before I deploy my sales agent, I want to make sure none of its stored memories contain API keys, passwords, or other secrets. It's a B2B outreach assistant — can you run a health check on these 120 memory entries and tell me what needs to be redacted?”
Resolving contradictory customer preferences
“My customer service agent seems to be giving inconsistent answers — I think its memory has contradictions. Can you audit these 80 memories from my e-commerce support bot and flag any conflicting facts so I know which ones to delete?”
PII audit for compliance review
“I need to make sure my AI scheduling assistant isn't storing any personal data it shouldn't have. Can you check these 200 memories for PII or sensitive personal information and give me a health grade and a list of what to clean up?”
Technical details
Endpoint
POSThttps://a-upgradenet.com/x402/memory-health?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit and sanitize AI agent memory stores before deployment, compliance reviews, or periodic hygiene checks — especially when secrets, PII, contradictions, or stale data may have accumulated. Prefer it over generic LLM prompting when you need structured issue categorization, severity ratings, and actionable cleanup plans with IDs tied back to original memory entries.
Side effects
- Empty or missing 'memories' array returns a validation error
- Exceeding 300 memory items results in rejection
- Malformed memory objects missing required 'text' field cause parse errors
- Payment failure or insufficient USDC balance blocks the request
- Ambiguous or very short memory texts may produce inaccurate grading
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| purpose | string | What the agent is for (improves the relevance check). |
| memories | array |
Output
Schema · Response
{
"type": "json",
"example": {
"grade": "C",
"score": 62,
"issues": [
{
"ids": [
"m3"
],
"type": "secret",
"action": "redact",
"severity": "critical"
},
{
"ids": [
"m1",
"m2"
],
"type": "contradiction",
"action": "delete",
"severity": "high"
}
],
"status": "completed",
"summary": {
"vague": 0,
"secrets": 1,
"duplicates": 0,
"personal_data": 0,
"contradictions": 1
},
"cleanup_plan": {
"delete": [
"m2"
],
"redact": [
"m3"
],
"rewrite": []
},
"cleaned_memories": [
{
"id": "m1",
"text": "Customer Ana prefers delivery after 6pm"
},
{
"id": "m3",
"text": "[REDACTED_SECRET]"
}
]
}
}Tags
x402
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