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preference-and-memory

Captures and evolves user preferences with confidence levels. Maintains Voice of the Customer model with exact language, dissatisfaction and aspiration signals. Handles promotion/demotion, global vs project scoping, auto memory system, and Omi wearable data integration.

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Files included (4)

  • SKILL.md4.1 KB
  • brian-decision-model.md6.6 KB
  • brian-voc-data.md2.8 KB
  • wisdom-and-human-psychology.md7.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

04 — Preference and Memory

Capture and evolve user preferences with confidence levels, maintaining a Voice of the Customer model scoped globally or per project.

Auto-memory system

Persistent file-based memory at /Users/Apple/.claude/projects/<encoded-path>/memory/. Write directly via Write tool.

Memory types

  • user — role, goals, responsibilities, knowledge
  • feedback — guidance on how to approach work (corrections AND confirmations)
  • project — ongoing initiatives, bugs, incidents, who/why/when
  • reference — pointers to external resources

Capture triggers

  • User explicitly says "remember X" / "save Y" → save immediately
  • Correction ("no not that", "don't") → feedback memory
  • Confirmation of unusual approach ("yes exactly", "perfect") → feedback memory
  • New role / preference / responsibility detail → user memory
  • Project milestone / decision / deadline → project memory
  • External system reference ("check the Linear project X") → reference memory

Memory file format

---
name: {short-kebab-case-slug}
description: {one-line summary — used for relevance ranking}
metadata:
  type: {user | feedback | project | reference}
---

{memory content}

For feedback/project: lead with rule/fact, then **Why:** line + **How to apply:** line.

Memory routing

  • Universal (across all projects) → ~/.claude/
  • Project-specific → ./.claude/ (path-scoped)
  • Project memory file → ~/.claude/projects/<encoded-path>/memory/<name>.md + index in MEMORY.md

MEMORY.md index

One-line pointer per file:

- [Title](file.md) — one-line hook

Keep under 200 lines (lines after 200 truncated).

Confidence levels

  • 0.95-1.0 — directly stated by Brian
  • 0.85-0.95 — strongly implied by pattern (3+ confirmations)
  • 0.70-0.85 — inferred from one signal
  • <0.70 — speculative, verify before acting

Below 0.70 → ask AskUserQuestion before persisting.

Voice of the Customer model

  • Exact language Brian uses ("pick ONE", "Hey not Hi", "always find 50 more things")
  • Dissatisfaction signals (corrections, re-issued prompts)
  • Aspiration signals (stated goals, ideal-world descriptions)
  • Stylistic preferences (brevity, sharpness, no preamble)

Brian's preferences (cite from rules/brian-preferences.md)

  • Pick ONE, never options
  • Never ask permission, silence = approval
  • "Hey" not "Hi", no preamble
  • Code complete, never truncate
  • Priority: simplicity > cost > speed > compatibility
  • Open-source only
  • Side repos auto-push; emdash projects user-push

Promotion / demotion

  • Memory recurring across 3+ projects → promote to rule (~/.claude/plugins/heymegabyte-agent-skills/rules/)
  • Rule contradicted by repeated correction → demote to memory or remove
  • Per rules/prompt-as-training-signal.md

Stale memory

  • Memory describing now-incorrect facts (renamed function, removed flag, retired service) → update OR delete
  • Per rules/prompt-as-training-signal.md § Before recommending from memory

Omi wearable integration (future)

  • Capture Brian's voice notes as candidate memory entries
  • Auto-tag by inferred type
  • Surface for review before commit
  • Path: ~/.claude/_omi-inbox/<timestamp>.md

Capture protocol (every prompt)

  1. Scan prompt for capture triggers
  2. Determine memory type
  3. Write file w/ frontmatter
  4. Add index entry to MEMORY.md
  5. Cross-link siblings via [[name]]
  6. Per rules/prompt-as-training-signal.md — extract BEFORE doing requested work

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