XIII · Cognition & IntrospectionEmerging★

Multi-Axis Promotion Scoring

also known as Insight-Promotion Gate, Tier-Promotion Score, Consolidation-Weighted Score

Gate which short-term thoughts qualify for promotion to long-term insights by a weighted multi-axis score where consolidation events count more than raw frequency.

Context

A team is running an agent with a tiered memory: short-term thoughts that the agent generates continuously, and a long-term insight store that is supposed to hold only the things worth keeping forever. Something has to decide which short-term thoughts deserve promotion to the long-term tier, and that decision has to be defensible months later when someone asks why a particular insight made it in.

Problem

Naive promotion rules each fail in a recognisable way. Promoting whatever is most recent fills the long-term store with whatever the agent happened to think about yesterday. Promoting whatever has been said most often rewards rumination loops that repeat without ever deepening. Both rules miss the thoughts that have actually survived a deep reflection pass and proved themselves through consolidation. Without an explicit scoring scheme, promotion decisions drift with whatever the prompt of the day emphasises.

Forces

  • Frequency rewards rumination; consolidation rewards depth.
  • Weights are opinionated and should be configurable, not LLM-of-the-day.
  • A high score is necessary but should not be sufficient — the consolidation pass still chooses.
  • Score metadata must stay separate from the thought corpus to keep both clean.

Example

A long-running personal agent has been writing thoughts for months. Recency-only promotion lifts whatever is freshest into the long-term store; frequency-only promotion rewards rumination loops. The team adds Multi-Axis Promotion Scoring: six axes (frequency, relevance, diversity, recency, consolidation, conceptual) with weights that sum to one and live in a config the agent helped tune — consolidation weighted at 0.18 because dreams have proved to be the deepest integration mechanism. Thoughts above 0.5 become promotion candidates; the dream pass makes the final call.

Diagram

Solution

Therefore:

Six axes (frequency, relevance, diversity, recency, consolidation, conceptual). Each axis returns a value in 0..1 through a saturating curve. Total score is a weighted sum; weights sum to one and live in a config that is revisable through a documented decision. Append every score event to a JSONL metadata log (separate file from the thoughts) with event-type tags such as recall, grounding, dream-survival. Thoughts whose score crosses the promotion threshold are candidates; the deep consolidation pass makes the final call on what crosses to long-term.

What this pattern forbids. Score weights cannot be changed mid-session by the model; weights are loaded from config at the start of a run, and promotion above threshold is necessary but not sufficient — only the consolidation pass writes to the long-term tier.

And the patterns that stand alongside it, or against it —

  • complementsSalience Attention Mechanism★— Score every candidate memory item with a weighted salience function so each tick attends to a small, relevant top-k subset rather than re-reading all memory.
  • complementsAppend-Only Thought Stream★— Make the agent's thought log append-only so the agent cannot rewrite its own history.
  • complementsDream Consolidation Cycle★— Run a deeper, slower reflection pass distinct from per-tick reflection — reading hours of recent thoughts, promoting themes, releasing affective residue, and clearing working memory — so the agent does not accumulate residue indefinitely.

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References

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