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Arcanea-LabsArcanea-Labs/Starlight-Intelligence-System/skills/memory/memory-consolidation/SKILL.md

memory/memory-consolidation

Skill10 starsChanged 2 months agoMITView on GitHub

Use when optimizing vault storage, archiving stale data, or deduplicating entries — consolidates related entries and ensures memory remains high-quality and retrievable. Inspired by AI-Ops working/episodic/semantic/procedural patterns. Default skill for Starlight Prime.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Default for: Starlight Prime

    line 15
  2. Distinctive:

    Update skills based on accumulated learnings

    line 43
  3. Distinctive:

    Update all references to point to the kept entry

    line 52
  4. Distinctive:

    Vault: All vaults (operates on all vaults)

    line 70

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

Memory Consolidation

"The art of remembering is the art of forgetting what doesn't matter."

When This Skill Activates

  • Optimizing vault storage, archiving old entries, deduplicating
  • Keywords: "consolidate", "optimize memory", "clean up", "archive", "deduplicate"
  • Default for: Starlight Prime

What This Skill Does

Optimizes the Starlight Vaults by consolidating related entries, archiving stale data, deduplicating, and ensuring memory remains high-quality and retrievable. Inspired by AI-Ops research on memory consolidation patterns (Working -> Episodic -> Semantic -> Procedural).

Procedures

Procedure 1: Memory Hierarchy Consolidation

Following the AI-Ops memory hierarchy:

  1. Working Memory (current session context)
    • Review items in current context
    • Identify what should be promoted to persistent storage
  2. Episodic Memory (specific events/sessions)
    • Review Session Notes older than 30 days
    • Extract lasting insights, archive the rest
    • Promote patterns to Semantic Memory
  3. Semantic Memory (general knowledge/facts)
    • Review vault entries for accuracy
    • Merge related entries into comprehensive entries
    • Promote proven patterns to Procedural Memory
  4. Procedural Memory (how-to knowledge)
    • Review skill effectiveness
    • Update skills based on accumulated learnings
    • Archive deprecated procedures

Procedure 2: Deduplication

  1. Scan vaults for entries with high similarity
  2. Compare content, timestamps, and confidence scores
  3. For duplicates: keep the entry with highest confidence
  4. Merge unique details from discarded duplicates
  5. Update all references to point to the kept entry
  6. Log deduplication actions for audit

Procedure 3: Quality Assessment

  1. Calculate vault health metrics:
    • Entry count per vault
    • Average confidence score
    • Oldest entry age
    • Index accuracy
    • Retrieval success rate
  2. Identify low-quality entries (low confidence, never retrieved)
  3. Recommend actions: consolidate, archive, or remove
  4. Generate vault health report
  5. Store report in Operational Vault

Integration Points

  • Vault: All vaults (operates on all vaults)
  • Agents: Prime (authorizes consolidation), Sage (knowledge quality)
  • Notes: Archives old notes, creates consolidation reports

Quality Criteria

  • Did consolidation reduce total entries without losing knowledge?
  • Are remaining entries higher quality?
  • Were no high-confidence entries accidentally removed?
  • Is the vault healthier after consolidation?

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