mm-consolidate

name	mm-consolidate
description	Scans memories for recurring patterns and proposes consolidation (merge, identity update, or shadow candidate)
user-invocable	true

mm-consolidate

Consolidation as integration — the operation that promotes raw extracted memories into structural identity content (CV7.E4.S3).

Memories accumulate over time. Patterns repeat. The same insight lands in five conversations as five isolated memories, none of which reaches the identity layer where it could actually change how the mirror responds. Consolidation is the bridge. This skill surfaces those clusters, proposes a structural move, and waits for explicit acknowledgment before writing anything.

Promotion mechanism: manual-by-acknowledgment. The scan is automatic; the promotion is not. Every proposal must be reviewed and accepted (or rejected) before it changes the database. This is intentional — identity updates are meaningful acts.

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Usage

/mm-consolidate [--journey <slug>] [--layer <layer>] [--limit <n>]
/mm-consolidate apply <proposal_id>
/mm-consolidate reject <proposal_id>
/mm-consolidate list [--status pending|accepted|rejected]

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1. Scan for proposals

uv run python -m memory consolidate scan \
  [--journey <slug>] \
  [--layer <layer>] \
  [--limit 5] \
  [--threshold 0.75]

This clusters semantically similar memories and calls the LLM to propose one of:

• merge: distill a redundant cluster into one sharper memory
• identity_update: encode a persistent pattern into an identity layer (ego/behavior, etc.)
• shadow_candidate: mark a tension/avoidance cluster for the mm-shadow pass

Each proposal is printed and stored with status='pending'.

Default filters: no journey or layer filter (all memories). Threshold 0.75. Limit 5 proposals.

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2. Present each proposal to Vinícius

For each proposal, show:

• The source memories (title, type, date)
• The proposed action and target (if identity_update: which layer/key)
• The rationale
• The proposed content

Ask: accept as-is / edit / reject?

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3. Apply or reject

Accept as-is:

uv run python -m memory consolidate apply <proposal_id>

Accept with edited content:

uv run python -m memory consolidate apply <proposal_id> \
  --content "User-revised version of the proposed content"

Reject:

uv run python -m memory consolidate reject <proposal_id>

What happens on acceptance:

• merge: creates a merged memory; source memories advance to integrated
• identity_update: appends to the identity layer; source memories advance to acknowledged
• shadow_candidate: source memories advance to candidate for the next mm-shadow pass

Rejected proposals leave source memories unchanged.

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4. List consolidation history

uv run python -m memory consolidate list [--status pending|accepted|rejected] [--limit 20]

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Notes

• The skill uses the same model as extraction (Gemini Flash via OpenRouter). LLM calls are logged to llm_calls when MEMORY_LOG_LLM_CALLS=1.
• Proposal IDs can be abbreviated to their first 8 characters.
• Memories with readiness_state='integrated' are excluded from clustering.
• Run with --threshold 0.65 to surface more (and looser) clusters; raise to 0.85 for tighter ones.
• For shadow-specific work, use mm-shadow (CV7.E4.S4) after candidates are established.