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.

248 stars

Best use case

claudemem-orchestration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using claudemem-orchestration should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/claudemem-orchestration/SKILL.md --create-dirs "https://raw.githubusercontent.com/MadAppGang/claude-code/main/plugins/code-analysis/skills/claudemem-orchestration/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/claudemem-orchestration/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How claudemem-orchestration Compares

Feature / Agentclaudemem-orchestrationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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 <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:

```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)

Related Skills

task-orchestration

248
from MadAppGang/claude-code

Track progress in multi-phase workflows with Tasks system. Use when orchestrating 5+ phase commands, managing iteration loops, tracking parallel tasks, or providing real-time progress visibility. Trigger keywords - "phase tracking", "progress", "workflow", "multi-step", "multi-phase", "tasks", "tracking", "status".

claudemem-search

248
from MadAppGang/claude-code

⚡ PRIMARY TOOL for semantic code search AND structural analysis. NEW: AST tree navigation with map, symbol, callers, callees, context commands. PageRank ranking. Recommended workflow: Map structure first, then search semantically, analyze callers before modifying.

test-skill

248
from MadAppGang/claude-code

A test skill for validation testing. Use when testing skill parsing and validation logic.

bad-skill

248
from MadAppGang/claude-code

This skill has invalid YAML in frontmatter

release

248
from MadAppGang/claude-code

Plugin release process for MAG Claude Plugins marketplace. Covers version bumping, marketplace.json updates, git tagging, and common mistakes. Use when releasing new plugin versions or troubleshooting update issues.

openrouter-trending-models

248
from MadAppGang/claude-code

Fetch trending programming models from OpenRouter rankings. Use when selecting models for multi-model review, updating model recommendations, or researching current AI coding trends. Provides model IDs, context windows, pricing, and usage statistics from the most recent week.

Claudish Integration Skill

248
from MadAppGang/claude-code

**Version:** 1.0.0

transcription

248
from MadAppGang/claude-code

Audio/video transcription using OpenAI Whisper. Covers installation, model selection, transcript formats (SRT, VTT, JSON), timing synchronization, and speaker diarization. Use when transcribing media or generating subtitles.

final-cut-pro

248
from MadAppGang/claude-code

Apple Final Cut Pro FCPXML format reference. Covers project structure, timeline creation, clip references, effects, and transitions. Use when generating FCP projects or understanding FCPXML structure.

ffmpeg-core

248
from MadAppGang/claude-code

FFmpeg fundamentals for video/audio manipulation. Covers common operations (trim, concat, convert, extract), codec selection, filter chains, and performance optimization. Use when planning or executing video processing tasks.

statusline-customization

248
from MadAppGang/claude-code

Configuration reference and troubleshooting for the statusline plugin — sections, themes, bar widths, and script architecture

technical-audit

248
from MadAppGang/claude-code

Technical SEO audit methodology including crawlability, indexability, and Core Web Vitals analysis. Use when auditing pages or sites for technical SEO issues.