Using Forgetful Memory

Forgetful is a semantic memory system using Zettelkasten (atomic note) principles. This skill guides effective memory usage.

When to Query Memory

Query memory proactively when:

• Starting work on a project (check for existing context)
• User references past work, decisions, or discussions
• Encountering a problem that may have been solved before
• Implementing patterns that may already be documented
• Needing context about preferences or approaches

Use execute_forgetful_tool("query_memory", {...}) with:

• query: Natural language search terms
• query_context: Why you're searching (improves ranking)
• include_links: true (to see connected knowledge)

When to Create Memory

Create memories for knowledge worth preserving:

• Important decisions with rationale (importance 8-9)
• Technical patterns or approaches (importance 7-8)
• Architectural choices (importance 9-10)
• Preferences and workflows (importance 8-9)
• Project milestones (importance 6-7)
• Solutions to non-trivial problems (importance 7-8)

Do NOT create memories for:

• Temporary context (current file paths, transient issues)
• Common knowledge available elsewhere
• Trivial or throwaway information
• Content that changes frequently

Atomic Memory Principles

Each memory must pass the atomicity test:

1. Can you understand it at first glance?
2. Can you title it in 5-50 words?
3. Does it represent ONE concept/fact/decision?

Constraints

Field	Limit	Guidance
Title	200 chars	Short, searchable phrase
Content	2000 chars	Single concept (~300-400 words)
Context	500 chars	WHY this matters
Keywords	10 max	For semantic clustering
Tags	10 max	For categorization

Importance Scoring

Score	Use For
9-10	Personal facts, foundational patterns
8-9	Critical solutions, major decisions
7-8	Useful patterns, preferences
6-7	Milestones, specific solutions
5-6	Minor context (use sparingly)

Query Before Create

Always check for existing memories before creating:

execute_forgetful_tool("query_memory", {
  "query": "<topic of potential new memory>",
  "query_context": "Checking for existing memories before creating",
  "k": 5
})

If similar memory exists:

• Update it instead of creating duplicate
• Or mark it obsolete if superseded
• Or link new memory to existing one

Announcing Memory Operations

When creating a memory (importance >= 7), announce:

💾 Saved to memory: "[title]"
   Tags: [tags]
   Related: [auto-linked memory titles]

When querying, summarize:

Found X memories about [topic]:
- [Memory 1]: [brief insight]
- [Memory 2]: [brief insight]

Content That's Too Long

If content exceeds 2000 chars:

1. Use create_document for full content
2. Extract 3-5 atomic memories as entry points
3. Link memories to document via document_ids

Example: Architecture overview (document) → separate memories for each layer/decision.