# Memory Recall

> 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…".

- Skill: `eternnoir/memory-recall` (Agent Skill)
- Install (CLI): `npx skillmds@latest add eternnoir/memory-recall`
- Raw SKILL.md: https://api.skillmd.com/api/skills/eternnoir/memory-recall/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: eternnoir (https://skillmd.com/u/eternnoir)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/eternnoir/memory-recall

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# 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.