recall-memory

senlima-sun's avatarfrom senlima-sun

Search and retrieve from memory. Use when user asks about past conversations, "what did we discuss", "find my notes about", "remember when", or needs historical context.

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[Memory and Context Management]

When & Why to Use This Skill

The recall-memory skill enables Claude to access a persistent local memory store to search and retrieve information from past interactions. It solves the problem of context loss between sessions, allowing the AI to maintain continuity, remember specific user decisions, and provide historical context for ongoing projects or personal notes.

Use Cases

  • Project Continuity: Retrieve specific action items or architectural decisions discussed in previous coding sessions to ensure development stays on track.
  • Knowledge Retrieval: Search through historical notes or 'spaces' to find specific information, such as health discussions, meeting summaries, or research findings.
  • Contextual Debugging: Recall previous error logs or debugging steps shared in past conversations to avoid repeating failed solutions.
  • Consistency Verification: Check past context before making new recommendations to ensure they align with previously established preferences or constraints.
namerecall-memory
descriptionSearch and retrieve from memory. Use when user asks about past conversations, "what did we discuss", "find my notes about", "remember when", or needs historical context.
allowed-toolsmcp__aiii__recall_memories, mcp__aiii__list_spaces

Recall from Memory

Search and retrieve previously saved memories from aiii's local store.

When to Use

  • User asks about previous conversations
  • User needs context from past sessions
  • User wants to find specific notes or decisions
  • Before making a decision that might contradict past context

Instructions

  1. Parse the user's query for:

    • Keywords and topics
    • Time references ("yesterday", "last week", "when we discussed X")
    • Space hints ("my work notes", "health stuff")

  2. Formulate the search:

    • Extract primary search terms
    • Identify space filter if mentioned
    • Determine result limit (default 5-10)

  3. Call recall_memories tool:

    {
  "query": "search terms",
  "space_id": "space_xxx", // optional
  "limit": 10
}

  4. Present results clearly:

    • Show title and date for each result
    • Include brief summary preview
    • Indicate the source (claude-code, claude-desktop, etc.)
    • Group by space if multiple spaces returned

  5. Offer to expand:

    • Ask if user wants full content of any specific memory
    • Offer to narrow search if too many results
    • Suggest related searches if no results found

Result Format

## Found 3 memories

### Work Space
1. **Auth refactoring: JWT to session-based** (Jan 7, 2026)
   > Refactored authentication from JWT to session-based approach...
   Source: claude-code | Tags: auth, jwt

2. **Rate limiting implementation** (Jan 6, 2026)
   > Added sliding window rate limiter to API endpoints...
   Source: claude-code | Tags: api, security

### Health Space
3. **Vitamin D discussion** (Jan 5, 2026)
   > Discussed optimal vitamin D levels and supplementation...
   Source: claude-desktop | Tags: vitamins, supplements

No Results Handling

If no memories match:

  1. Acknowledge the search found nothing
  2. Suggest broadening search terms
  3. List available spaces that might contain relevant info
  4. Offer to help reformulate the query

Example Interaction

User: "What did we discuss about authentication last week?"

Claude:

  1. Parses: topic="authentication", time="last week"
  2. Searches: query: "authentication", limit: 10
  3. Finds 2 results in Work space
  4. Presents formatted results
  5. Offers: "Want me to show the full content of any of these?"