Agent-Skills.md

Agent Skills: Memory Recall

Search and recall memories. Auto-triggered when a topic relates to past discussions or the user asks about previous context.

UncategorizedID: legacybridge-tech/claude-plugins/memory-recall

Repository

legacybridge-tech/claude-plugins
legacybridge-techLicense: MIT
5

Install this agent skill to your local

pnpm dlx add-skill https://github.com/legacybridge-tech/claude-plugins/tree/HEAD/engram/skills/memory-recall

Skill Files

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engram/skills/memory-recall/SKILL.md

Skill Metadata

Name
memory-recall
Description
Search and recall memories from the Engram files. Trigger when a topic may relate to past discussions, when the user references previous context, or when the user asks "do you remember…".

Memory Recall

Search and retrieve relevant memories from the memory files.

When to Use

Trigger when:

  • The current topic might relate to past discussions
  • The user references something from a previous conversation
  • You're uncertain about context that may have been discussed before
  • The user asks "do you remember..." or similar queries

Do NOT guess or assume — search memory files first, then respond with confidence.

Note: memory_preferences.md is already auto-loaded into context via the @ reference in CLAUDE.md — you usually do not need to re-read it here unless the user just updated it.

Workflow

1. Read Configuration

Read .claude/memory-settings.json to get the configured file names.

2. Extract Search Keywords

From the current conversation context, identify:

  • Key topics, names, technologies, or concepts
  • Time references ("last week", "when we discussed X")
  • Specific terms the user mentioned

3. Search in Parallel

Execute searches across all three files simultaneously:

Preferences File

  • Read the full file (it's small, designed to be loaded entirely)
  • Extract relevant sections

Conversations File

  • Use Grep to search for keywords
  • Results are in reverse chronological order (newest first)
  • Look for matching ### YYYY-MM-DD entries and their content

Long-Term Memory File

  • Use Grep to search for keywords
  • Check across all subsections (milestones, decisions, lessons, etc.)

4. Synthesize Results

Combine findings from all files into a coherent response:

  • Prioritize the most relevant and recent information
  • Cross-reference between files (e.g., a preference change might relate to a conversation)
  • Present information naturally — don't list "found in file X"

5. Response Style

Integrate recalled memories naturally into your response. Examples:

Good: "Based on our previous discussion, you decided to use PostgreSQL for this project. You also mentioned preferring connection pooling via PgBouncer."

Bad: "I searched memory_conversations.md and found an entry from 2025-01-15 that mentions PostgreSQL. I also found in memory_longterm.md under Architecture Decisions..."

The user should feel like you genuinely remember, not like you're reading from a database.