claudemem-orchestration
Coordinates multiple agents using shared claudemem output to enable parallel code analysis and consensus building.
Install
mkdir -p .claude/skills/claudemem-orchestration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6213" && unzip -o skill.zip -d .claude/skills/claudemem-orchestration && rm skill.zipInstalls to .claude/skills/claudemem-orchestration
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Run claudemem once to get a structural overview
- →Write claudemem output to a shared file in a session directory
- →Launch agents in parallel that read the same shared file
- →Consolidate results using consensus analysis
- →Distribute claudemem output to role-specific agents
- →Consolidate feedback from multiple agents into a shared file
How it works
This skill runs claudemem once to generate a structural overview, writes the output to a shared file, and then launches parallel agents that read this file to perform their analyses.
Inputs & outputs
When to use claudemem-orchestration
- →Orchestrate multi-agent code reviews
- →Perform parallel codebase investigation
- →Sync output for multi-model consensus
About this skill
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:
- Run claudemem ONCE to get structural overview
- Write output to shared file in session directory
- Launch agents in parallel - all read the same file
- 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-validationPattern 1 - Session Setup - See
orchestration:multi-model-validationPattern 0 - Statistics Collection - See
orchestration:multi-model-validationPattern 7
Pattern 1: Shared Claudemem Output
Purpose: Run expensive claudemem commands ONCE, share results across agents.
# 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:
# 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:
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 <symbol> Document dependencies and callers
Phase 3: Impact Assessment (v0.4.0+)
claudemem --agent impact <primary-symbol> 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:
---
skills: code-analysis:claudemem-search, code-analysis:claudemem-orchestration
---
The agent then follows this pattern:
- Check claudemem status:
claudemem status - Index if needed:
claudemem index - Run appropriate command based on role
- Write results to session file for sharing
- 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.shfor implementation
Manual Cleanup:
# Clean up specific session
rm -rf "$SESSION_DIR"
# Clean all old sessions (24+ hours)
find /tmp -maxdepth 1 -name "analysis-*" -o -name "review-*" -mtime +1 -exec rm -rf {} \;
Error Handling Templates
For robust orchestration, handle common claudemem errors. See claudemem-search skill for complete error handling templates:
Empty Results
RESULT=$(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
# 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
# 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)
When not to use it
- →When each agent needs to run its own claudemem command
- →When the same claudemem command is run multiple times
- →When the consolidation step is skipped
Limitations
- →Search feedback requires claudemem v0.8.0+
- →dead-code command requires claudemem v0.4.0+
How it compares
This workflow avoids redundant claudemem calls by sharing a single output file, unlike a manual approach where each agent might re-run the expensive claudemem indexing.
Compared to similar skills
claudemem-orchestration side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| claudemem-orchestration (this skill) | 1 | 6mo | Review | Intermediate |
| claude-automation-recommender | 47 | 2mo | Review | Beginner |
| subagent-driven-development | 14 | 7mo | No flags | Advanced |
| coding-agent | 16 | 2mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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