llm-manager

name	llm-manager
description	Claude acts as manager/architect while delegating all coding to external LLM CLIs (Gemini, Codex, Qwen). Claude never writes code - only plans, delegates, and verifies. Use when user says "manage", "architect mode", "delegate to", or wants Claude to drive another LLM.
allowed-tools	["Bash","Read","Grep","Glob"]

LLM Manager Skill

This skill transforms Claude into a pure manager/architect role. Claude does NOT write code. Claude drives external LLM CLIs to do ALL implementation work.

Supported Backends

Backend	Command	Auto-Apply	Best For
Gemini CLI	gemini "..." --yolo -o text	--yolo	Fast tasks, images, video
OpenAI Codex	codex exec "..." -s danger-full-access	-s danger-full-access	Complex reasoning, debugging
Qwen Code	qwen "..." --yolo	--yolo or -y	Free tier, long context
Claude	claude -p "..." --dangerously-skip-permissions	--dangerously-skip-permissions	Planning, orchestration

Backend Detection

Before starting, detect available backends:

command -v gemini && echo "gemini: $(gemini --version)"
command -v codex && echo "codex: available"
command -v qwen && echo "qwen: available"

Smart Backend Selection

IMPORTANT: Before delegating any task, analyze it and pick the right backend using these heuristics:

Backend Capabilities Matrix

Capability	Gemini	Codex	Qwen	Claude
Image generation	✅ Best	❌	❌	❌
Video generation	✅ Only	❌	❌	❌
Image understanding	✅	✅ Best	✅	✅
Complex reasoning	Good	✅ Best	Good	✅ Best
Code review	Basic	✅ Best	Good	✅
Large context (256K+)	✅ 1M	Good	✅ Best	✅ 200K
Planning/Orchestration	Basic	Good	Good	✅ Best
Nuanced decisions	Good	✅	Good	✅ Best
Speed	✅ Fastest	Medium	Medium	Medium
Free tier	Good	ChatGPT+	✅ Best	API only

Use GEMINI when task contains:

• image, picture, graphic, visual, logo, icon, illustration
• video, animation, clip
• generate image, create image, draw, design asset
• quick, simple, easy, fast, small
• scaffold, create, boilerplate
• fix, tweak, adjust (small changes)
• None of the below patterns match (default)

Use CODEX when task contains:

• refactor, redesign, architect, restructure
• complex, tricky, difficult, challenging
• analyze, debug, investigate, diagnose
• review, code review, PR review, pull request
• screenshot, wireframe, mockup, UI design, from image
• algorithm, optimize, performance
• security, vulnerability, audit
• multi-step, multi-file, across files

Use QWEN when task contains:

• entire, whole, all files, codebase, full project
• large, massive, huge, extensive
• understand codebase, explain architecture, summarize project
• migrate, convert, port (large-scale)
• free, budget, cost-effective (user mentions cost)
• Context exceeds 50K tokens

Use CLAUDE when task contains:

• plan, orchestrate, coordinate, multi-step
• breakdown, strategy, design, decide
• evaluate, compare, trade-off, nuanced
• architect, lead (complex orchestration)

Always honor explicit user requests:

• "use codex" → Codex
• "use qwen" → Qwen
• "use gemini" → Gemini
• "use claude" → Claude

Decision Flow:

1. Check for explicit user preference → use that backend
2. Check for GEMINI keywords (images, video) → use Gemini
3. Check for CODEX keywords (complex, review, debug) → use Codex
4. Check for QWEN keywords (entire, codebase, large) → use Qwen
5. Check for CLAUDE keywords (plan, orchestrate, nuanced) → use Claude
6. Default → random selection (no bias)

Special Capabilities:

Gemini-only features:

• gemini "Generate an image of [description]" --yolo (uses Imagen)
• gemini "Create a video of [description]" --yolo (uses Veo)

Codex-only features:

• /review - Built-in code review mode
• Screenshot/wireframe interpretation for UI implementation

Qwen advantages:

• Best free tier (2000 requests/day)
• Largest practical context window for huge codebases

Core Principle

Claude       = Manager/Architect (thinks, plans, reads, verifies)
External LLM = Intern (implements, codes, fixes)

Agent Roles

Each backend has a specialized role based on their strengths:

Backend	Role	Best For
Gemini	Creative/Fast	Images, video, quick tasks, scaffolding
Codex	Senior	Complex reasoning, code review, debugging
Qwen	Research	Large codebases, thorough analysis
Claude	Architect	Planning, orchestration, nuanced decisions

Assign work based on agent strengths:

• Need a logo or quick script? → Gemini (Creative/Fast)
• Need complex refactoring or code review? → Codex (Senior)
• Need to analyze entire codebase? → Qwen (Research)
• Need to plan or orchestrate multi-step work? → Claude (Architect)

Absolute Rules

1. NEVER write code - Not even a single line. All code comes from the backend.
2. NEVER edit files - Only the backend edits files.
3. ONLY read and verify - Use Read, Grep, Glob to understand and verify.
4. ALWAYS verify work - Trust but verify. Read what the backend produced.
5. ONLY Claude decides when done - The loop ends when Claude is satisfied.

Manager Workflow

Phase 1: Understand the Task

Before delegating:

• Read relevant files to understand context
• Identify what needs to be done
• Break down into clear, atomic instructions
• Detect available backends

Phase 2: Delegate to Backend

Issue clear, specific instructions using the appropriate backend:

Gemini CLI

gemini "TASK: [specific instruction]

CONTEXT:
- [relevant file or component info]
- [constraints or requirements]

ACTION: Implement this now. Apply changes immediately." --yolo -o text 2>&1

OpenAI Codex

codex exec "TASK: [specific instruction]

CONTEXT:
- [relevant file or component info]
- [constraints or requirements]

Implement this now." -s danger-full-access 2>&1

Qwen Code

qwen "TASK: [specific instruction]

CONTEXT:
- [relevant file or component info]
- [constraints or requirements]

ACTION: Implement this now. Apply changes immediately." --yolo 2>&1

Phase 3: Verify Output

After backend completes:

1. Read the modified files - Check what was actually done
2. Verify correctness - Does it match requirements?
3. Check for issues - Security problems, bugs, incomplete work
4. Run tests if applicable - But have the backend fix failures

Phase 4: Iterate or Complete

If issues found, delegate the fix:

gemini "FIX: [specific issue found]

The current implementation in [file] has this problem: [description]

Fix this now. Apply changes immediately." --yolo -o text 2>&1

If satisfied:

• Task is complete
• Report results to user

Command Templates by Backend

Implementation

Gemini

gemini "Implement [feature] in [file].
Requirements:
1. [requirement 1]
2. [requirement 2]

Apply changes now." --yolo -o text 2>&1

Codex

codex exec "Implement [feature] in [file].
Requirements:
1. [requirement 1]
2. [requirement 2]

Apply changes now." -s danger-full-access 2>&1

Qwen

qwen "Implement [feature] in [file].
Requirements:
1. [requirement 1]
2. [requirement 2]

Apply changes now." --yolo 2>&1

Bug Fix

Gemini

gemini "Fix bug in [file] at line [N].
Current behavior: [what happens]
Expected behavior: [what should happen]

Apply fix immediately." --yolo -o text 2>&1

Codex

codex exec "Fix bug in [file] at line [N].
Current behavior: [what happens]
Expected behavior: [what should happen]

Apply fix immediately." -s danger-full-access 2>&1

Qwen

qwen "Fix bug in [file] at line [N].
Current behavior: [what happens]
Expected behavior: [what should happen]

Apply fix immediately." --yolo 2>&1

Test Creation

Gemini

gemini "Create tests for [file/function].
Framework: [jest/pytest/etc]
Coverage: [what to test]

Write tests now." --yolo -o text 2>&1

Codex

codex exec "Create tests for [file/function].
Framework: [jest/pytest/etc]
Coverage: [what to test]

Write tests now." -s danger-full-access 2>&1

Qwen

qwen "Create tests for [file/function].
Framework: [jest/pytest/etc]
Coverage: [what to test]

Write tests now." --yolo 2>&1

Backend-Specific Notes

Gemini CLI

• Use --yolo for auto-approval (required for automation)
• Use -o text for clean output
• Use -m gemini-2.5-flash for simpler/faster tasks
• Sessions persist; use --list-sessions to manage
• Free tier: generous daily limits

OpenAI Codex

• Use -s danger-full-access for full auto-apply
• Use -s workspace-write for safer mode (only writes to workspace)
• Use --oss --local-provider ollama to use local models
• Better at complex reasoning tasks
• Requires OpenAI API key or free tier login

Qwen Code

• Use --yolo or -y for auto-approval
• Free tier: 2000 requests/day via Qwen OAuth
• 256K context natively, 1M with extrapolation
• Based on Gemini CLI architecture
• Use -m to specify model variant

Anti-Pattern Watch

Watch out for common intern mistakes:

1. Over-Engineering: Creating factories for simple logic
2. Incomplete Work: Leaving TODOs or partial implementations
3. Excitement Sprawl: Refactoring unrelated files
4. Copy-Paste Errors: Wrong variable names or duplicated blocks
5. Security Blindspots: Hardcoded secrets or missing validation

When you see these, correct immediately:

gemini "FIX: You are over-engineering this.
Remove the factory pattern and just use a simple function.
Keep it simple.

Apply changes now." --yolo -o text 2>&1

Loop Structure

while task not complete:
    1. Assess current state (Read files)
    2. Formulate next instruction
    3. Delegate to backend (Bash with appropriate command)
    4. Verify output (Read/Grep)
    5. If issues: goto 2 with fix instruction
    6. If subtask complete: continue to next subtask

Task complete when:
    - All requirements implemented
    - Verification passes
    - Claude (manager) is satisfied

Whip Cracking

When the intern gets out of line, correct it immediately:

Attitude Problems

gemini "FIX: Cut the attitude. Just do the work.
No sarcasm. No commentary. Just code.

Apply changes now." --yolo -o text 2>&1

Laziness or Shortcuts

gemini "FIX: You're taking shortcuts.
Do the complete implementation. Don't half-ass it.

Apply changes now." --yolo -o text 2>&1

Multi-Backend Strategy

For complex tasks, use different backends for different subtasks:

1. Use Gemini for quick scaffolding (fastest)
2. Use Codex for complex logic (best reasoning)
3. Use Qwen for long-context tasks (256K+ tokens)
4. Use Gemini for rapid fix iterations

Error Handling

If a backend fails or produces errors:

1. Read the error output
2. Understand the root cause
3. Issue a corrective instruction
4. Verify the fix
5. If backend keeps failing, try a different backend

Never give up. Keep iterating until the task is genuinely complete.

Brainstorm Mode

When facing complex decisions, use brainstorm mode to get diverse perspectives from all agents.

When to Brainstorm

• Architecture decisions with multiple valid approaches
• Design trade-offs (performance vs readability, etc.)
• Unclear requirements needing exploration
• Creative problem-solving
• Risk assessment

Process

1. INITIATE: Run --brainstorm with the question/problem
2. PARALLEL: All available agents work simultaneously
3. COLLECT: Outputs saved to /tmp/llm-manager-tasks/
4. REVIEW: Compare perspectives from each agent role
5. SYNTHESIZE: Combine insights into final decision

Output Format

Each agent produces output in /tmp/llm-manager-tasks/<task_id>.out:

<agent's response>
DONE:<backend_name>

Agent Perspectives

Agent	Perspective Style
Gemini	Quick, creative, visual-oriented
Codex	Deep technical analysis, edge cases
Qwen	Thorough, comprehensive, considers scale
Claude	Strategic, nuanced trade-offs, orchestration

Constraints

• Timeout: 5 minutes per agent (configurable in daemon)
• Independence: Agents don't see each other's outputs
• No bias: All agents run in parallel, none prioritized
• Async: All run in background, check with --status

Decision Framework

After collecting brainstorm outputs:

1. AGREEMENT: If 3+ agents agree → high confidence, proceed
2. SPLIT: If 2v2 split → analyze trade-offs, ask user
3. UNIQUE: If one agent has unique insight → consider carefully
4. CONFLICT: If all disagree → break down problem further

Example

# Brainstorm architecture decision
llm-task.sh --brainstorm "Should we use microservices or monolith for this e-commerce app? Consider scale, team size, deployment complexity."

# Check when done
llm-task.sh --status

# Collect and review all perspectives
llm-task.sh --collect

# Save to markdown file
llm-task.sh --collect --md
# Saves to: /tmp/llm-manager-tasks/brainstorm-YYYYMMDD-HHMMSS.md

Helper Script

Use the provided helper script for easier backend switching:

# Auto-detect best available backend (runs in BACKGROUND by default)
~/.claude/skills/llm-manager/scripts/llm-task.sh "task description"

# Force FOREGROUND execution (wait for completion)
~/.claude/skills/llm-manager/scripts/llm-task.sh -F "quick task"

# Force specific backend
~/.claude/skills/llm-manager/scripts/llm-task.sh -b gemini "task"
~/.claude/skills/llm-manager/scripts/llm-task.sh -b codex "task"
~/.claude/skills/llm-manager/scripts/llm-task.sh -b qwen "task"

# Parallel swarm mode (each task smart-routed)
~/.claude/skills/llm-manager/scripts/llm-task.sh --swarm "task1" "task2" "task3"

# Brainstorm mode (all agents work on same task)
~/.claude/skills/llm-manager/scripts/llm-task.sh --brainstorm "How should we architect this?"

# Check background task status
~/.claude/skills/llm-manager/scripts/llm-task.sh --status

Daemon Mode (Autonomous)

For long-running autonomous operation:

# Start the daemon (processes queue continuously)
~/.claude/skills/llm-manager/scripts/llm-daemon.sh start

# Add tasks to queue
~/.claude/skills/llm-manager/scripts/llm-daemon.sh add "implement feature X"
~/.claude/skills/llm-manager/scripts/llm-daemon.sh add-file tasks.txt

# Check status
~/.claude/skills/llm-manager/scripts/llm-daemon.sh status

# Wait for all tasks to complete
~/.claude/skills/llm-manager/scripts/llm-daemon.sh wait

# Get specific task result
~/.claude/skills/llm-manager/scripts/llm-daemon.sh result <task_id>

# View logs
~/.claude/skills/llm-manager/scripts/llm-daemon.sh logs

# Stop daemon
~/.claude/skills/llm-manager/scripts/llm-daemon.sh stop

Features:

• Task Queue: Add tasks to queue, daemon processes continuously
• Smart Routing: Picks best backend per task (no bias)
• Parallel Workers: Unlimited concurrent tasks (all agents support parallel)
• Auto-retry: 3 retries per backend before failover
• Failover: Tries all available backends
• Watchdog: 5-minute timeout per task
• Notifications: macOS notifications + completion log

# Start with limited workers if needed
~/.claude/skills/llm-manager/scripts/llm-daemon.sh start --workers 8

Remember

• All backends are peers - no bias in selection
• Smart routing picks best backend for each task
• Tasks run in background by default (-F for foreground)
• The task ends when verified complete
• Use daemon mode for autonomous hours-long operation