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Memory Protocol Skill

Gives any AI agent a persistent, structured memory using a single Markdown file (agent-memory.md). Defines when to read memory, how to write new entries, rules for keeping it clean, and a /dream consolidation procedure for when the file grows too large.

Purpose

Long-running agents lose context between sessions. This skill solves that by:

  • Reading memory before answering domain-specific questions
  • Writing structured entries after significant tasks
  • Replacing stale entries instead of appending duplicates
  • Consolidating the file when it exceeds 200 lines via /dream

When to Use This Skill

Activate when the agent:

  • Receives a thematic question ("how does X work in this project?")
  • Completes a significant task (new feature, debug session, config change)
  • Is asked to remember something
  • Encounters /dream command

Activation keywords: "remember", "what do you know about", "update memory", "/dream", any domain-specific question the agent might already know the answer to

Memory File Location

Default path (adapt to your vault/project structure):

/data/obsidian-vault/ProjectName/agent-memory.md

Entry Format

### YYYY-MM-DD - Title
- Scope: user | project | session | team
- Content: ...
- Source: observation
- Expires: permanent

The /dream Command

When agent-memory.md exceeds 200 lines:

  1. Read the full file
  2. Group entries by topic, remove outdated duplicates
  3. Save a snapshot of the old version to Memory/dream-YYYY-MM-DD.md
  4. Write a condensed agent-memory.md (target: 50–70 lines)

This prevents context window bloat without losing historical data.

Rules

  • Replace, don't append: If a newer fact supersedes an old entry on the same topic, edit the file
  • Never store: API keys, tokens, passwords, PII
  • Be concrete: Entries should be actionable in a future session, not vague notes