Delegation

Unified Delegation Skill

⛔ CRITICAL: No Claude Subagents (MANUAL ENFORCEMENT)

NEVER spawn Claude models (Haiku, Sonnet, Opus) as subagents.

⛔ The deny rules in .claude/settings.local.json DO NOT enforce this. ⛔ Manual verification required before EVERY Task() call.

See CLAUDE.md for the pre-Task() checklist and fallback protocol.

Provider Selection Matrix

Automatic Fallback Protocol

When a Task() call fails, follow this chain (NEVER fallback to Haiku/Sonnet/Opus):

Example:

# ❌ WRONG - Kimi failed, fell back to Haiku
Task(model="kimi", ...) → Error
Task(model="haiku", ...) → VIOLATION

# ✅ CORRECT - Kimi failed, fell back to GLM
Task(model="kimi", ...) → Error
Task(model="minimax", ...) → Success

If all cheap models fail:

1. Do the work yourself (Claude)
2. Document why all subagents failed
3. Flag for manual investigation with user
4. NEVER use Haiku/Sonnet/Opus as fallback

Quick Decision Flow

┌─ Is it reasoning/decisions? ──────────────────┐
│  YES → Claude does it directly                │
│  NO  → Delegate to subagent ↓                 │
├───────────────────────────────────────────────┤
│                                               │
│  ┌─ Does it need vision? ───────────────────┐ │
│  │  YES → Kimi K2.5 (or GLM-4.6v fallback)  │ │
│  │  NO  ↓                                   │ │
│  └──────────────────────────────────────────┘ │
│                                               │
│  ┌─ Is it complex/creative? ────────────────┐ │
│  │  Complex → Kimi K2.5                     │ │
│  │  Creative → GLM-4.7                      │ │
│  │  Simple → MiniMax                        │ │
│  └──────────────────────────────────────────┘ │
└───────────────────────────────────────────────┘

Provider Profiles

Kimi K2.5 (Most Capable)

Context: 256K tokens | Vision: Yes | Thinking mode: Yes

Best for:

• Complex multi-step reasoning
• Batch image analysis (10+ images)
• Tasks requiring deep understanding
• Fallback for failed GLM tasks

Launcher: .\scripts\start-kimi.ps1

API Config:

Base URL: https://api.moonshot.cn/anthropic/
Models: kimi-k2.5-thinking, kimi-k2-turbo-preview

GLM-4.7 (Creative)

Context: 128K tokens | Vision: GLM-4.6v variant | Thinking mode: Yes

Best for:

• Creative brainstorming
• Mathematical reasoning (95.7% AIME 2025)
• Parallel batch tasks
• Tool use orchestration

MCP: .cursor/mcp.json (GLM-4.6v configured)

MiniMax M2.1 (Fast & Cheap)

Context: 128K tokens | Vision: VLM API | Speed: Fastest

Best for:

• Quick web searches
• Simple file exploration
• Structured data extraction
• Code review for blind spots

Launcher: .\scripts\start-claude-minimax.ps1

MCP: .cursor/mcp.json (MiniMax configured)

Delegation Patterns

Pattern 1: Research → Claude Decides

1. Claude receives task requiring research
2. Claude spawns MiniMax: "Find all uses of X in codebase"
3. MiniMax returns findings
4. Claude reasons and implements

Pattern 2: Batch Vision Analysis

1. Claude needs to analyze 20 sprites
2. Claude spawns Kimi K2.5: "Analyze quality of each sprite"
3. Kimi returns analysis for all 20
4. Claude makes decisions based on report

Pattern 3: Creative Exploration

1. Claude needs alternative approaches
2. Claude spawns GLM-4.7: "Brainstorm 5 solutions for X"
3. GLM returns creative options
4. Claude selects and refines best approach

Pattern 4: Code Review

1. Claude writes code
2. Claude spawns MiniMax: "Check for bugs, edge cases, security issues"
3. MiniMax returns concerns
4. Claude addresses or dismisses with reasoning

Parallel Delegation

Launch multiple subagents in a single message:

Task(prompt="Research X", subagent_type="general-purpose")  ←─┐
Task(prompt="Research Y", subagent_type="general-purpose")  ←─┼─ Parallel
Task(prompt="Research Z", subagent_type="general-purpose")  ←─┘

Rules:

• Independent tasks → parallel
• Dependent tasks → sequential
• Never chain Claude subagents

Background Execution (Token Suspension)

Problem: Claude tokens burn while waiting for subagent results. Solution: Use run_in_background=true + end turn early.

Pattern: Fire-and-Retrieve

1. Claude receives task requiring research
2. Task(prompt="...", run_in_background=true) → returns output_file
3. Claude ends turn: "Research agent dispatched. Say 'continue' for results."
4. User says "continue"
5. TaskOutput(task_id="...", block=true) → retrieves results
6. Claude synthesizes and responds

When to Use Background Execution

Token Savings Calculation

Blocking:     Claude waits 60s = 60s of Opus tokens burned
Background:   Claude ends turn = 0s of Opus tokens burned
              (subagent tokens are 50x cheaper)

Example Usage

# Fire (spawn and end turn immediately)
Task(
  prompt="Analyze all 20 sprites in assets/sprites/",
  subagent_type="general-purpose",
  run_in_background=true
)
→ Returns: {task_id: "abc123", output_file: "/path/to/output"}

# ... Claude ends turn, tells user to say "continue" ...

# Retrieve (on next turn)
TaskOutput(task_id="abc123", block=true)
→ Returns: Full subagent analysis

Token Economics

Key insight: 1 hour Claude exploration = 50 hours subagent exploration (cost).

Common Mistakes

Integration with Other Skills

• /skill kimi-k2.5 - Detailed Kimi setup and patterns
• /skill minimax-mcp - MiniMax MCP integration details
• /skill token-efficient-delegation - Full token economics
• /skill subagent-best-practices - General subagent patterns

[Opus 4.5 - 2026-01-29]