Coder Memory Recall

⚠️ EXECUTION CONTEXT: This Skill MUST be executed using Task tool with subagent_type="general-purpose". Runs in separate context to avoid polluting main conversation.

Purpose: Retrieve universal coding patterns from file-based memory at ~/.claude/skills/coder-memory-store/.

Key Architecture: SKILL.md + README.md files form a tree guideline structure - read overviews first, navigate to specific files as needed. Very effective for progressive disclosure.

Keep SKILL.md lean: Provide overview and reference other files. When this file becomes unwieldy, split content into separate files and reference them. Trust Claude to read detailed files only when needed.

When to Use:

• •Before starting complex, multi-step implementations
• •When encountering unfamiliar technical problems
• •User explicitly says "--coder-recall" or "--recall" (Claude decides if universal or project-specific, may use both)
• •Need architectural guidance or debugging strategies

REMEMBER: Failures are as valuable as successes. Look for both #success and #failure tags when searching memories.

When NOT to Use:

• •Routine or trivial tasks
• •Just recalled similar knowledge recently
• •Project-specific questions (use project-memory-recall)

PHASE 0: Understand Memory Structure

Read ~/.claude/skills/coder-memory-store/SKILL.md to understand current organization.

Memory types available:

• •episodic/ - Concrete coding events
• •procedural/ - Workflows and processes
• •semantic/ - Principles and patterns

PHASE 1: Construct Search Strategy

If user provided explicit query: Use it to determine which memory type(s) to search

If inferring from context: Analyze task to choose:

• •Need specific past experience? → Search episodic
• •Need step-by-step process? → Search procedural
• •Need general principle/pattern? → Search semantic
• •Unclear? → Search all three

Query keywords: Extract 3-8 core concepts (no filler words)

PHASE 2: Search for Relevant Memories

Step 0 (Optional): Try Vector Search First

If Qdrant MCP server available, try semantic search for file hints:

1. •

   Construct vector query - Use full summary for better semantic matching:

   • •If user provided query: Use their question/description as-is
   • •If inferring from task: Write 2-3 sentence summary of what you're looking for
   • •Include key concepts, technical terms, and problem description
   • •Keep concise but descriptive (not just keywords, not entire context)
2. •

   Call search_memory MCP tool:

   code

   search_memory(
       query="<2-3 sentence summary of what you're looking for>",
       memory_level="coder",
       limit=5
   )
   

3. •

   Extract file_path hints and similarity scores from top results

4. •

   Use hints to guide file-based search:

   • •Vector results are hints only (may be outdated/wrong)
   • •Always proceed to file-based navigation below
   • •Use file_path hints to prioritize which files to read first
   • •If <3 results or tool unavailable: Continue to file-based navigation below

IMPORTANT: Vector search is an ADDITIONAL tool to help find similar memories, not a replacement for progressive disclosure. Always use file-based navigation to verify and retrieve complete information.

File-Based Navigation (Primary Method)

For each target memory type:

1. •Read README.md (if exists) in memory type directory
2. •Identify relevant subdirectories based on query (use file_path hints if available)
3. •Read targeted files:
   • •Use Grep to search for keywords across files (prioritize hinted paths if available)
   • •Use Read to load promising files
   • •Progressive disclosure: Read READMEs first, then specific files

Do NOT read entire memory tree - use filesystem tools intelligently.

PHASE 3: Extract Relevant Memories

Collect top 3 most relevant memories matching query.

Relevance criteria:

• •Keyword match quality
• •Context similarity to current task
• •Actionability for current situation

PHASE 4: Check If Refactoring Needed

Signs memory needs reorganization:

• •Took >5 file reads to find relevant memories
• •Found duplicates in multiple files
• •Unrelated content mixed in same file
• •Difficult to navigate structure

If reorganization needed: Invoke general-purpose agent to refactor memory structure.

Refactoring prompt:

Refactor coder-memory-store file structure at ~/.claude/skills/coder-memory-store/.

Current issues: [describe what made recall difficult]

Actions needed:
- Merge duplicate memories
- Reorganize files by topic (max 2-level depth)
- Update README.md files as overviews
- Ensure episodic/procedural/semantic separation is clear

Maintain all existing memory content - only reorganize structure.

PHASE 5: Present Results

Format:

🔍 Coder Memory Recall Results

**Query**: <keywords or user question>
**Memory Types Searched**: <episodic/procedural/semantic>
**Results Found**: <number>

---

## Result 1: [Title]

**Type**: <Episodic/Procedural/Semantic>
**Source**: <file path>

<Full memory content>

**Relevance**: <1-2 sentences explaining why this matches query>

---

## Result 2: [Title]

[Same format]

---

## Application Guidance

<2-3 sentences synthesizing results and actionable next steps for current task>

If no results found:

🔍 Coder Memory Recall Results

**Query**: <keywords>
**Results Found**: 0 relevant memories

No universal patterns matched your query in coder memory.

**Suggestions**:
- Try broader search terms
- Check if this is project-specific (use project-memory-recall)
- Proceed with standard approaches and store insights after completion

If refactoring triggered:

⚙️ Memory Refactoring Triggered

Memory structure was reorganized during recall to improve future searches.
<report refactoring actions taken>

Tool Usage

CRITICAL: Invoke via Task tool with general-purpose agent. Never execute directly in main context.