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Aionis currently ships as a local-first Lite Runtime for developer machines and self-managed deployments.
Core ConceptsFeedback Attribution

Feedback Attribution

Aionis does not treat every successful run as proof that every retrieved memory helped.

Feedback attribution links four facts:

guide exposure -> host use -> outcome -> memory lifecycle evidence

What The Host Must Track

FieldWhy
guide_trace_idIdentifies the exact guide exposure.
exposed memory IDsDefines what memory was available to the Agent.
actually used memory IDsPrevents false credit for unused recall.
run_idLinks feedback to a real execution run.
outcome and verifier signalDistinguishes successful reuse from harmful reuse.

Why Aionis Is Strict

Feedback is rejected when the host attributes outcome to memory that was not exposed by the referenced guide. This is intentional. Otherwise the dataset would mix real usage with guesses.

import { feedbackFromGuide } from "@aionis/sdk"; const usedMemoryIds = result.usedMemoryIds ?? []; if (usedMemoryIds.length > 0) { await aionis.feedback(feedbackFromGuide({ guide, run_id, outcome: "positive", reason: "The Agent used the active path and verifier passed.", used_memory_ids: usedMemoryIds, used_surface: "use_now", })); }

Positive, Negative, Neutral

OutcomeMeaning
positiveThe memory helped or was consistent with a successful run.
negativeThe memory contributed to a bad or rejected outcome.
neutralThe memory was observed but effect is unclear.

Negative feedback does not automatically delete memory. It becomes lifecycle evidence that can demote, suppress, or route memory to inspect-first.

What This Enables

Feedback attribution powers:

  • memory decision traces
  • memory use receipts
  • admission dataset export
  • future learned admission policy
  • Agent Flight Recorder replay
  • controlled forgetting and reactivation