# Claudemem Orchestration > Use when orchestrating multi-agent code analysis with claudemem. Run claudemem once, share output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping. - Skill: `tomevault-io/claudemem-orchestration` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/claudemem-orchestration` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/claudemem-orchestration/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/claudemem-orchestration --- # Claudemem Multi-Agent Orchestration **Version:** 1.1.0 **Purpose:** Coordinate multiple agents using shared claudemem output ## Overview When multiple agents need to investigate the same codebase: 1. **Run claudemem ONCE** to get structural overview 2. **Write output to shared file** in session directory 3. **Launch agents in parallel** - all read the same file 4. **Consolidate results** with consensus analysis This pattern avoids redundant claudemem calls and enables consensus-based prioritization. **For parallel execution patterns, see:** `orchestration:multi-model-validation` skill ## Claudemem-Specific Patterns This skill focuses on claudemem-specific orchestration. For general parallel execution: - **4-Message Pattern** - See `orchestration:multi-model-validation` Pattern 1 - **Session Setup** - See `orchestration:multi-model-validation` Pattern 0 - **Statistics Collection** - See `orchestration:multi-model-validation` Pattern 7 ### Pattern 1: Shared Claudemem Output **Purpose:** Run expensive claudemem commands ONCE, share results across agents. ```bash # Create unique session directory (per orchestration:multi-model-validation Pattern 0) SESSION_ID="analysis-$(date +%Y%m%d-%H%M%S)-$(head -c 4 /dev/urandom | xxd -p)" SESSION_DIR="/tmp/${SESSION_ID}" mkdir -p "$SESSION_DIR" # Run claudemem ONCE, write to shared files claudemem --agent map "feature area" > "$SESSION_DIR/structure-map.md" claudemem --agent test-gaps > "$SESSION_DIR/test-gaps.md" 2>&1 || echo "No gaps found" > "$SESSION_DIR/test-gaps.md" claudemem --agent dead-code > "$SESSION_DIR/dead-code.md" 2>&1 || echo "No dead code" > "$SESSION_DIR/dead-code.md" # Export session info echo "$SESSION_ID" > "$SESSION_DIR/session-id.txt" ``` **Why shared output matters:** - Claudemem indexing is expensive (full AST parse) - Same index serves all queries in session - Parallel agents reading same file = no redundant computation ### Pattern 2: Role-Based Agent Distribution After running claudemem, distribute to role-specific agents: ``` # Parallel Execution (ONLY Task calls - per 4-Message Pattern) Task: architect-detective Prompt: "Analyze architecture from $SESSION_DIR/structure-map.md. Focus on layer boundaries and design patterns. Write findings to $SESSION_DIR/architect-analysis.md" --- Task: tester-detective Prompt: "Analyze test gaps from $SESSION_DIR/test-gaps.md. Prioritize coverage recommendations. Write findings to $SESSION_DIR/tester-analysis.md" --- Task: developer-detective Prompt: "Analyze dead code from $SESSION_DIR/dead-code.md. Identify cleanup opportunities. Write findings to $SESSION_DIR/developer-analysis.md" All 3 execute simultaneously (3x speedup!) ``` ### Pattern 3: Consolidation with Ultrathink ``` Task: ultrathink-detective Prompt: "Consolidate analyses from: - $SESSION_DIR/architect-analysis.md - $SESSION_DIR/tester-analysis.md - $SESSION_DIR/developer-analysis.md Create unified report with prioritized action items. Write to $SESSION_DIR/consolidated-analysis.md" ``` ### Pattern 4: Consolidated Feedback Reporting (v0.8.0+) When multiple agents perform searches, consolidate feedback for efficiency. **Why Consolidate?** - Avoid duplicate feedback submissions - Single point of failure handling - Cleaner session cleanup **Shared Feedback Collection:** Each agent writes feedback to a shared file in the session directory: ```bash # Agent writes feedback entry (atomic with flock) report_agent_feedback() { local query="$1" local helpful="$2" local unhelpful="$3" # Use file locking to prevent race conditions ( flock -x 200 printf '%s|%s|%s\n' "$query" "$helpful" "$unhelpful" >> "$SESSION_DIR/feedback.log" ) 200>"$SESSION_DIR/feedback.lock" } # Usage in agent report_agent_feedback "$SEARCH_QUERY" "$HELPFUL_IDS" "$UNHELPFUL_IDS" ``` **Orchestrator Consolidation:** After all agents complete, the orchestrator submits all feedback: ```bash consolidate_feedback() { local session_dir="$1" local feedback_log="$session_dir/feedback.log" # Skip if no feedback collected [ -f "$feedback_log" ] || return 0 # Check if feedback command available (v0.8.0+) if ! claudemem feedback --help 2>&1 | grep -qi "feedback"; then echo "Note: Search feedback requires claudemem v0.8.0+" return 0 fi local success=0 local failed=0 while IFS='|' read -r query helpful unhelpful; do # Skip empty lines [ -n "$query" ] || continue if timeout 5 claudemem feedback \ --query "$query" \ --helpful "$helpful" \ --unhelpful "$unhelpful" 2>/dev/null; then ((success++)) else ((failed++)) fi done < "$feedback_log" echo "Feedback: $success submitted, $failed failed" # Cleanup rm -f "$feedback_log" "$session_dir/feedback.lock" } # Call after consolidation consolidate_feedback "$SESSION_DIR" ``` **Multi-Agent Workflow Integration:** ``` Phase 1: Session Setup └── Create SESSION_DIR with feedback.log Phase 2: Parallel Agent Execution └── Agent 1: Search → Track → Write feedback entry └── Agent 2: Search → Track → Write feedback entry └── Agent 3: Search → Track → Write feedback entry Phase 3: Results Consolidation └── Consolidate agent outputs Phase 4: Feedback Consolidation (NEW) └── Read all feedback entries from log └── Submit each to claudemem └── Report success/failure counts Phase 5: Cleanup └── Remove SESSION_DIR (includes feedback files) ``` **Best Practices Update:** **Do:** - Use file locking for concurrent writes (`flock -x`) - Consolidate feedback AFTER agent completion - Report success/failure counts - Clean up feedback files after submission **Don't:** - Submit feedback from each agent individually - Skip the version check - Block on feedback submission failures - Track feedback for non-search commands (map, symbol, callers, etc.) ## Role-Based Command Mapping | Agent Role | Primary Commands | Secondary Commands | Focus | |------------|------------------|-------------------|-------| | Architect | `map`, `dead-code` | `context` | Structure, cleanup | | Developer | `callers`, `callees`, `impact` | `symbol` | Modification scope | | Tester | `test-gaps` | `callers` | Coverage priorities | | Debugger | `context`, `impact` | `symbol`, `callers` | Error tracing | | Ultrathink | ALL | ALL | Comprehensive | ## Sequential Investigation Flow For complex bugs or features requiring ordered investigation: ``` Phase 1: Architecture Understanding claudemem --agent map "problem area" Identify high-PageRank symbols (> 0.05) Phase 2: Symbol Deep Dive For each high-PageRank symbol: claudemem --agent context Document dependencies and callers Phase 3: Impact Assessment (v0.4.0+) claudemem --agent impact Document full blast radius Phase 4: Gap Analysis (v0.4.0+) claudemem --agent test-gaps --min-pagerank 0.01 Identify coverage holes in affected code Phase 5: Action Planning Prioritize by: PageRank * impact_depth * test_coverage ``` ## Agent System Prompt Integration When an agent needs deep code analysis, it should reference the claudemem skill: ```yaml --- skills: code-analysis:claudemem-search, code-analysis:claudemem-orchestration --- ``` The agent then follows this pattern: 1. **Check claudemem status**: `claudemem status` 2. **Index if needed**: `claudemem index` 3. **Run appropriate command** based on role 4. **Write results to session file** for sharing 5. **Return brief summary** to orchestrator ## Best Practices **Do:** - Run claudemem ONCE per investigation type - Write all output to session directory - Use parallel execution for independent analyses (see `orchestration:multi-model-validation`) - Consolidate with ultrathink for cross-perspective insights - Handle empty results gracefully **Don't:** - Run same claudemem command multiple times - Let each agent run its own claudemem (wasteful) - Skip the consolidation step - Forget to clean up session directory (automatic TTL cleanup via `session-start.sh`) ## Session Lifecycle Management **Automatic TTL Cleanup:** The `session-start.sh` hook automatically cleans up expired session directories: - Default TTL: 24 hours - Runs at session start - Cleans `/tmp/analysis-*`, `/tmp/review-*` directories older than TTL - See `plugins/code-analysis/hooks/session-start.sh` for implementation **Manual Cleanup:** ```bash # Clean up specific session rm -rf "$SESSION_DIR" # Clean all old sessions (24+ hours) find /tmp -maxdepth 1 -name "analysis-*" -o -name "review-*" -mtime +1 -exec rm -rf {} \; ``` ## Error Handling Templates For robust orchestration, handle common claudemem errors. See `claudemem-search` skill for complete error handling templates: ### Empty Results ```bash RESULT=$(claudemem --agent map "query" 2>/dev/null) if [ -z "$RESULT" ] || echo "$RESULT" | grep -q "No results found"; then echo "No results - try broader keywords or check index status" fi ``` ### Version Compatibility ```bash # Check if command is available (v0.4.0+ commands) if claudemem --agent dead-code 2>&1 | grep -q "unknown command"; then echo "dead-code requires claudemem v0.4.0+" echo "Fallback: Use map command instead" fi ``` ### Index Status ```bash # Verify index before running commands if ! claudemem status 2>&1 | grep -qE "[0-9]+ (chunks|symbols)"; then echo "Index not found - run: claudemem index" exit 1 fi ``` **Reference:** For complete error handling patterns, see templates in `code-analysis:claudemem-search` skill (Templates 1-5) --- **Maintained by:** MadAppGang **Plugin:** code-analysis v2.8.0 **Last Updated:** December 2025 (v1.1.0 - Search feedback protocol support) --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/madappgang) — claim your Tome and manage your conversions.