home / skills / madappgang / claude-code / agent-coordination-discipline

agent-coordination-discipline skill

/plugins/dev/skills/discipline/agent-coordination-discipline

This skill helps you decide when to launch or coordinate agents, select models, and implement delegation strategies for reliable task isolation.

npx playbooks add skill madappgang/claude-code --skill agent-coordination-discipline

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---
name: agent-coordination-discipline
description: "Use when deciding whether to launch an agent, selecting which agent to use, or coordinating multiple agents. Covers delegation criteria, PROXY_MODE patterns, task isolation, and agent selection strategies."
keywords: [agent-coordination, PROXY_MODE, task-isolation, delegation-criteria, multi-agent, external-model, claudish, orchestration, agent-selection, Task-tool, developer-agent, architect-agent, grok-code-fast, sonnet-4-5, thinking-budget]
created: 2026-01-20
updated: 2026-01-20
plugin: dev
type: discipline
difficulty: intermediate
---

# Agent Coordination Discipline

**Iron Law:** "NO AGENT LAUNCH WITHOUT CLEAR DELEGATION CRITERIA"

## When to Use

Use this skill when:
- Considering launching an agent with the Task tool
- Evaluating whether a task requires agent delegation
- Selecting between different agent types or external models
- Coordinating multiple agents in a workflow
- Implementing PROXY_MODE for external model delegation
- Debugging agent coordination failures

This skill prevents premature agent launches, redundant agent usage, and poor task isolation that wastes thinking budget and causes coordination failures.

## Red Flags (Violation Indicators)

- [ ] **Agent for single grep** - Launching agent to run one grep/glob command (trivial-task anti-pattern)
- [ ] **Missing PROXY_MODE model** - Using PROXY_MODE without explicit model name specification
- [ ] **No task isolation** - Agent task description lacks independent context or success criteria
- [ ] **No success criteria** - Task description doesn't define what "done" looks like
- [ ] **Default thinking pattern** - Not considering whether task needs deep thinking vs. fast execution
- [ ] **Multiple agents without coordination** - Launching 2+ agents without clear result routing plan
- [ ] **Result not used** - Launching agent but not routing/validating its output
- [ ] **Agent for trivial decision** - Using agent to make decision you could make directly
- [ ] **No tool exhaustion check** - Launching agent before trying native tools first
- [ ] **Missing timeout consideration** - Not evaluating if task needs extended thinking time
- [ ] **No error handling plan** - Not defining what happens if agent fails or returns partial results
- [ ] **Skill gap unclear** - Not identifying what specific expertise the agent provides

## Key Concepts

### 1. Agent vs. Native Tools Decision Tree

```
Does the task require:
├─ Single tool call (grep, read, edit)?
│  └─ ✗ NO AGENT - Use native tool directly
├─ 2-3 sequential tool calls?
│  └─ ✗ NO AGENT - Use tools directly in sequence
├─ Multi-step investigation with branching logic?
│  └─ ✓ AGENT - Task tool with developer/architect agent
├─ External model expertise (Grok, DeepSeek, etc.)?
│  └─ ✓ AGENT - PROXY_MODE pattern with model specification
├─ Parallel exploration of multiple code paths?
│  └─ ✓ AGENT - Multiple Task calls with coordination
└─ High-risk change needing isolation?
   └─ ✓ AGENT - Task tool with sandbox/review focus
```

### 2. Task Isolation Requirements

Every agent task must be independently executable:

**Bad (not isolated):**
```
Task: "Fix the bug we discussed earlier"
```

**Good (properly isolated):**
```
Task: "Debug the TypeError in src/components/UserProfile.tsx line 42.
Context: User reports 'Cannot read property name of undefined' when viewing profile page.
Evidence: Error occurs after recent commit abc123 that changed user data structure.
Success criteria: Identify root cause, propose fix, verify with test scenario."
```

### 3. PROXY_MODE Pattern

When delegating to external models via claudish:

**Structure:**
```
PROXY_MODE: {model_id}

{Task Description}

Context:
- {Relevant file paths}
- {Current state}
- {Related decisions}

Success Criteria:
- {What constitutes success}
- {Expected output format}

Constraints:
- {Time limits}
- {Tool restrictions}
- {Quality requirements}
```

**Example:**
```
PROXY_MODE: x-ai/grok-code-fast-1

Analyze the React component rendering performance issue in Dashboard.tsx.

Context:
- File: src/components/Dashboard.tsx (247 lines)
- Issue: Component re-renders 40+ times on data updates
- Recent changes: Added real-time WebSocket updates in commit f4a2c1b

Success Criteria:
- Identify unnecessary re-renders (provide line numbers)
- Propose memoization strategy
- Estimate performance improvement

Constraints:
- Max 3 minutes analysis time
- Focus on React 19 compiler-friendly patterns
```

## When to Use Agents

### Multi-Step Investigation
**Trigger:** Task requires 5+ tool calls with conditional branching
**Agent:** developer, architect
**Example:** "Trace data flow through 3 layers to find where user.email becomes null"

### External Model Expertise
**Trigger:** Need specialized model capabilities (code speed, vision, reasoning)
**Agent:** PROXY_MODE with specific model
**Example:** "Use Grok Code Fast to refactor 15 files for consistency in < 2 minutes"

### Parallel Work
**Trigger:** Multiple independent tasks that can run simultaneously
**Agent:** Multiple Task calls with result aggregation
**Example:** "Analyze frontend performance (Task 1) while auditing API security (Task 2)"

### Risk Isolation
**Trigger:** High-risk changes needing review before merging to main workflow
**Agent:** review-focused agent with checkpoint
**Example:** "Evaluate if this database migration will cause downtime"

### Skill Gaps
**Trigger:** Current agent lacks specific skill that another agent has
**Agent:** specialist agent (security, performance, accessibility)
**Example:** "Launch accessibility agent to audit ARIA compliance"

## When NOT to Use Agents

### Single Grep/Glob
**Instead:** Use native Grep or Glob tool directly
```
# ✗ DON'T
Task: "Find all files using the deprecated API"

# ✓ DO
Grep("oldApiCall", output_mode: "files_with_matches", type: "js")
```

### Simple Tool Execution
**Instead:** Use tool directly
```
# ✗ DON'T
Task: "Read the config file and tell me the API URL"

# ✓ DO
Read("/path/to/config.json")
// Parse and extract apiUrl field
```

### Decision Already Made
**Instead:** Execute the decision
```
# ✗ DON'T
Task: "I think we should use React Query. What do you think?"

# ✓ DO
// Just implement React Query since decision is made
Write("src/hooks/useApiQuery.ts", reactQueryCode)
```

### Sequential Tool Calls
**Instead:** Chain tools directly
```
# ✗ DON'T
Task: "Find the function, read it, and edit it"

# ✓ DO
Grep("functionName", output_mode: "files_with_matches")
// => result: src/utils/helper.ts
Read("src/utils/helper.ts")
Edit("src/utils/helper.ts", old_string, new_string)
```

### Nuanced Context Required
**Instead:** Handle in current agent
```
# ✗ DON'T
Task: "Based on our earlier discussion about performance vs. maintainability trade-offs, decide if we should cache this"

# ✓ DO
// Current agent already has context, make decision directly
if (performanceIsCritical) {
  implementCaching()
}
```

## Agent Selection Matrix

| Task Type | Best Agent | Model | Reasoning |
|-----------|------------|-------|-----------|
| **Debugging errors** | developer | sonnet-4-5 | Deep reasoning, context retention |
| **Design review** | architect | sonnet-4-5 | System thinking, trade-off evaluation |
| **Code generation** | developer | grok-code-fast | Speed for repetitive patterns |
| **Multi-codebase analysis** | developer | sonnet-4-5 | Cross-repo understanding |
| **Performance profiling** | developer + PROXY_MODE | grok-code-fast | Fast scanning + specific optimization |
| **Security audit** | security (if available) | sonnet-4-5 | Nuanced threat modeling |
| **Documentation generation** | developer | grok-code-fast | Fast, straightforward task |
| **Refactoring (large scope)** | developer | sonnet-4-5 | Maintain consistency across changes |

## PROXY_MODE Pattern Details

### 1. Model Selection

**Fast Execution (< 2 min):**
- `x-ai/grok-code-fast-1` - Code generation, refactoring, simple analysis
- `anthropic/claude-3-5-haiku` - Quick decisions, data transformation

**Deep Reasoning (> 2 min):**
- `anthropic/claude-sonnet-4-5` - Complex debugging, architecture design
- `google/gemini-2.0-flash-thinking-exp-01-21` - Extended thinking budget

**Specialized:**
- Vision models - Screenshot analysis, diagram interpretation
- Code models - Language-specific optimization

### 2. Context Packaging

**Minimal (< 1000 tokens):**
- File paths only
- Error message
- Success criteria

**Moderate (1000-5000 tokens):**
- Key code snippets (< 50 lines)
- Related file structure
- Recent commit context

**Full (5000+ tokens):**
- Complete file contents
- Related test files
- Architecture documentation

### 3. Success Criteria Definition

**Must include:**
- **Output format** - JSON, markdown, code snippet, report
- **Completeness** - What must be covered
- **Quality bar** - Minimum acceptable quality
- **Constraints** - Time, token, tool limits

**Example:**
```
Success Criteria:
- Output: JSON array of {file, line, issue, suggestion}
- Completeness: All React components in src/ analyzed
- Quality: Each suggestion must include before/after code
- Constraints: Complete within 5 minutes, use only Read/Grep tools
```

### 4. Result Routing

**Pattern:**
```
1. Launch agent with PROXY_MODE
2. Capture result in variable or file
3. Validate result against success criteria
4. Route to next step:
   - If success: Use result in main workflow
   - If partial: Request clarification
   - If failure: Fall back to native tools
```

**Example:**
```
result = Task("PROXY_MODE: x-ai/grok-code-fast-1\n\nRefactor 10 components for React 19...")

if (result.contains("Refactored successfully")) {
  // Apply changes to codebase
  applyRefactorings(result.changes)
} else {
  // Fall back to manual refactoring
  manualRefactor()
}
```

## Task Isolation Checklist

Before launching an agent, verify:

- [ ] **Independent understanding** - Task description is self-contained (no "as discussed", "the bug we saw")
- [ ] **Success criteria defined** - Clear definition of what "done" looks like
- [ ] **Dependencies listed** - All required files, services, credentials specified
- [ ] **Result format specified** - Expected output structure (JSON, markdown, code, report)
- [ ] **Error handling clear** - What happens if agent fails or returns partial results
- [ ] **Timeout reasonable** - Time limit matches task complexity
- [ ] **Tool attempts exhausted** - Tried native tools first, agent is not premature
- [ ] **Model selection justified** - Chosen model matches task requirements (speed vs. reasoning)

## Examples

### Example 1: Bad Agent Usage (Python)

```python
# ✗ VIOLATION: Agent for single grep
Task: "Find all files importing the old database client"

# ✓ CORRECT: Use native tool
Grep("from old_db_client import", type: "py", output_mode: "files_with_matches")
```

### Example 2: Good Agent Usage (TypeScript)

```typescript
// ✓ CORRECT: Multi-step investigation with agent
Task: "Debug the race condition in WebSocket message handling.

Context:
- File: src/services/websocket.ts (342 lines)
- Issue: Messages arrive out of order 5% of the time
- Environment: Production only (not reproducible in dev)
- Recent changes: Added message batching in commit a3f9c21

Success Criteria:
- Identify race condition root cause (provide line numbers)
- Propose synchronization strategy
- Verify solution handles edge cases

Constraints:
- Max 10 minutes analysis
- Use Read, Grep, and Bash tools only
- No code changes (diagnosis only)"
```

### Example 3: PROXY_MODE with External Model (Go)

```go
// ✓ CORRECT: Fast refactoring with Grok
PROXY_MODE: x-ai/grok-code-fast-1

Refactor 15 handler functions in handlers/ to use consistent error handling pattern.

Context:
- Directory: internal/handlers/ (15 files, ~200 lines each)
- Current state: Inconsistent error responses (some use Error(), some use Errorf(), some return raw errors)
- Target pattern: Use custom AppError type with status codes and messages

Success Criteria:
- All 15 handlers use AppError consistently
- Preserve existing business logic (only change error handling)
- Provide git diff summary

Constraints:
- Complete within 3 minutes
- Use Read and Grep tools for analysis
- Return refactored code for all 15 files
```

## Integration with Other Skills

**Works with:**
- **verification-before-completion** - Validate agent results before marking tasks complete
- **systematic-debugging** - Use agents for multi-step debugging investigations
- **orchestration skills** - Multi-agent coordination patterns from orchestration plugin

**Prevents:**
- **Premature agent launches** - Check delegation criteria first
- **Agent thrashing** - Avoid launching agents that just launch more agents
- **Budget waste** - Don't use slow models for fast tasks or vice versa

## Anti-Patterns Table

| Anti-Pattern | ✗ Without Discipline | ✓ With Discipline |
|--------------|---------------------|-------------------|
| **Trivial task delegation** | Launch agent to run single grep | Use Grep tool directly |
| **Missing isolation** | "Fix the bug we discussed" | "Debug TypeError in UserProfile.tsx line 42: 'Cannot read property name of undefined'. Context: ..." |
| **No success criteria** | "Analyze the performance issue" | "Identify re-render causes (line numbers), propose memoization, estimate improvement %" |
| **Wrong model selection** | Use sonnet-4-5 for simple refactoring | Use grok-code-fast for speed |
| **No result validation** | Launch agent, assume success | Check result against success criteria, have fallback plan |
| **Coordination failure** | Launch 3 agents, hope they coordinate | Define result routing: Agent 1 → validate → Agent 2 → aggregate |

## Enforcement Mechanism

**Detection:**
1. Before Task tool call, check if task description includes success criteria
2. Before PROXY_MODE, verify model name is explicitly specified
3. Before agent launch, confirm native tools were attempted first
4. After agent completes, verify result is validated before use

**Correction:**
1. If missing success criteria → Add "Success Criteria:" section to task description
2. If trivial task → Cancel agent launch, use native tool
3. If wrong model → Reconsider model selection based on task requirements
4. If result unused → Add validation and routing logic

**Validation:**
```
Agent Task Checklist (all must be true):
✓ Task requires 5+ tool calls OR external model expertise
✓ Success criteria defined (output format, completeness, quality bar)
✓ Context is self-contained (no references to earlier discussion)
✓ Model selection justified (speed vs. reasoning trade-off considered)
✓ Result routing planned (validation + next steps)
✓ Error handling defined (fallback if agent fails)
✓ Native tools attempted first (or explicitly not applicable)
```

---

**Related Skills:**
- `verification-before-completion` - Validate agent results
- `systematic-debugging` - Multi-step debugging investigations
- `orchestration/multi-agent-orchestration` - Complex coordination patterns

**Version:** 1.0.0
**Last Updated:** 2026-01-20

Overview

This skill codifies when and how to launch agents, choose models, and coordinate multiple agents to avoid wasted compute and coordination failures. It enforces clear delegation criteria, task isolation, success criteria, and PROXY_MODE patterns for external model delegation. Use it to decide if a native tool suffices or an agent is justified and to structure agent tasks for reliable results.

How this skill works

It inspects proposed Task launches for delegation necessity, required tool calls, and whether success criteria and context are present. It validates PROXY_MODE usage by ensuring an explicit model selection and packages context, constraints, and expected output formats. It also enforces result routing, timeout handling, and fallback steps to native tools when agents fail or return partial results.

When to use it

  • Deciding whether to launch an agent or use native tools
  • Selecting a model or PROXY_MODE for external model delegation
  • Coordinating multiple agents or parallel Task calls
  • Designing isolated, independently executable agent tasks
  • Debugging coordination failures or agent thrashing

Best practices

  • Always define success criteria: output format, completeness, and quality bar
  • Prefer native tools for single-tool or simple sequential tool calls
  • Package self-contained context and list dependencies for every agent task
  • Select models by matching speed vs. reasoning needs (fast vs. deep-thinking models)
  • Specify timeouts, error handling, and fallback plans before launch

Example use cases

  • Multi-step investigation: trace data through layers requiring branching logic
  • PROXY_MODE delegation: fast code refactor using a grok-code-fast model
  • Parallel work: run independent audits (performance, security) with result aggregation
  • Risk isolation: run a review-focused agent for high-risk changes before merge
  • Skill-gap delegation: launch a specialist agent for security or accessibility audits

FAQ

How do I know when to use PROXY_MODE instead of a local agent?

Use PROXY_MODE when you need specialized external model capabilities (speed, vision, or deep reasoning) and always include an explicit model_id, context, constraints, and success criteria.

What counts as a trivial task that shouldn't use an agent?

Any task solvable with a single tool call (grep, read, edit) or 2–3 sequential tool calls should use native tools directly; agents are for multi-step, branching, parallel, or high-risk tasks.

What must a task description include before launching an agent?

A self-contained context, clear success criteria, dependencies, expected output format, timeout, error handling, and justification for the chosen model.