Claude-Code-Workflow/.claude/commands/workflow/tools/task-generate-agent.md

name, description, argument-hint, examples

name	description	argument-hint	examples
task-generate-agent	Autonomous task generation using action-planning-agent with discovery and output phases	--session WFS-session-id [--cli-execute]	/workflow:tools:task-generate-agent --session WFS-auth /workflow:tools:task-generate-agent --session WFS-auth --cli-execute

Autonomous Task Generation Command

Overview

Autonomous task JSON and IMPL_PLAN.md generation using action-planning-agent with two-phase execution: discovery and document generation. Supports both agent-driven execution (default) and CLI tool execution modes.

Core Philosophy

• Agent-Driven: Delegate execution to action-planning-agent for autonomous operation
• Two-Phase Flow: Discovery (context gathering) → Output (document generation)
• Memory-First: Reuse loaded documents from conversation memory
• MCP-Enhanced: Use MCP tools for advanced code analysis and research
• Pre-Selected Templates: Command selects correct template based on --cli-execute flag before invoking agent
• Agent Simplicity: Agent receives pre-selected template and focuses only on content generation

Execution Lifecycle

Phase 1: Discovery & Context Loading

⚡ Memory-First Rule: Skip file loading if documents already in conversation memory

Agent Context Package:

{
  "session_id": "WFS-[session-id]",
  "execution_mode": "agent-mode" | "cli-execute-mode",  // Determined by flag
  "task_json_template_path": "~/.claude/workflows/cli-templates/prompts/workflow/task-json-agent-mode.txt"
                           | "~/.claude/workflows/cli-templates/prompts/workflow/task-json-cli-mode.txt",
  // Path selected by command based on --cli-execute flag, agent reads it
  "session_metadata": {
    // If in memory: use cached content
    // Else: Load from .workflow/{session-id}/workflow-session.json
  },
  "analysis_results": {
    // If in memory: use cached content
    // Else: Load from .workflow/{session-id}/.process/ANALYSIS_RESULTS.md
  },
  "artifacts_inventory": {
    // If in memory: use cached list
    // Else: Scan .workflow/{session-id}/.brainstorming/ directory
    "synthesis_specification": "path or null",
    "topic_framework": "path or null",
    "role_analyses": ["paths"]
  },
  "context_package": {
    // If in memory: use cached content
    // Else: Load from .workflow/{session-id}/.process/context-package.json
  },
  "mcp_capabilities": {
    "code_index": true,
    "exa_code": true,
    "exa_web": true
  }
}

Discovery Actions:

1. Load Session Context (if not in memory)

   if (!memory.has("workflow-session.json")) {
     Read(.workflow/{session-id}/workflow-session.json)
   }
   

2. Load Analysis Results (if not in memory)

   if (!memory.has("ANALYSIS_RESULTS.md")) {
     Read(.workflow/{session-id}/.process/ANALYSIS_RESULTS.md)
   }
   

3. Discover Artifacts (if not in memory)

   if (!memory.has("artifacts_inventory")) {
     bash(find .workflow/{session-id}/.brainstorming/ -name "*.md" -type f)
   }
   

4. MCP Code Analysis (optional - enhance understanding)

   // Find relevant files for task context
   mcp__code-index__find_files(pattern="*auth*")
   mcp__code-index__search_code_advanced(
     pattern="authentication|oauth",
     file_pattern="*.ts"
   )
   

5. MCP External Research (optional - gather best practices)

   // Get external examples for implementation
   mcp__exa__get_code_context_exa(
     query="TypeScript JWT authentication best practices",
     tokensNum="dynamic"
   )
   

Phase 2: Agent Execution (Document Generation)

Pre-Agent Template Selection (Command decides path before invoking agent):

// Command checks flag and selects template PATH (not content)
const templatePath = hasCliExecuteFlag
  ? "~/.claude/workflows/cli-templates/prompts/workflow/task-json-cli-mode.txt"
  : "~/.claude/workflows/cli-templates/prompts/workflow/task-json-agent-mode.txt";

Agent Invocation:

Task(
  subagent_type="action-planning-agent",
  description="Generate task JSON and implementation plan",
  prompt=`
## Execution Context

**Session ID**: WFS-{session-id}
**Execution Mode**: {agent-mode | cli-execute-mode}
**Task JSON Template Path**: {template_path}

## Phase 1: Discovery Results (Provided Context)

### Session Metadata
{session_metadata_content}

### Analysis Results
{analysis_results_content}

### Artifacts Inventory
- **Synthesis Specification**: {synthesis_spec_path}
- **Topic Framework**: {topic_framework_path}
- **Role Analyses**: {role_analyses_list}

### Context Package
{context_package_summary}

### MCP Analysis Results (Optional)
**Code Structure**: {mcp_code_index_results}
**External Research**: {mcp_exa_research_results}

## Phase 2: Document Generation Task

### Task Decomposition Standards
**Core Principle**: Task Merging Over Decomposition
- **Merge Rule**: Execute together when possible
- **Decompose Only When**:
  - Excessive workload (>2500 lines or >6 files)
  - Different tech stacks or domains
  - Sequential dependency blocking
  - Parallel execution needed

**Task Limits**:
- **Maximum 10 tasks** (hard limit)
- **Function-based**: Complete units (logic + UI + tests + config)
- **Hierarchy**: Flat (≤5) | Two-level (6-10) | Re-scope (>10)

### Required Outputs

#### 1. Task JSON Files (.task/IMPL-*.json)
**Location**: .workflow/{session-id}/.task/
**Template**: Read from the template path provided above

**Task JSON Template Loading**:
\`\`\`
Read({template_path})
\`\`\`

**Important**:
- Read the template from the path provided in context
- Use the template structure exactly as written
- Replace placeholder variables ({synthesis_spec_path}, {role_analysis_path}, etc.) with actual session-specific paths
- Include MCP tool integration in pre_analysis steps
- Map artifacts based on task domain (UI → ui-designer, Backend → system-architect)

#### 2. IMPL_PLAN.md
**Location**: .workflow/{session-id}/IMPL_PLAN.md

**IMPL_PLAN Template**:
\`\`\`
$(cat ~/.claude/workflows/cli-templates/prompts/workflow/impl-plan-template.txt)
\`\`\`

**Important**:
- Use the template above for IMPL_PLAN.md generation
- Replace all {placeholder} variables with actual session-specific values
- Populate CCW Workflow Context based on actual phase progression
- Extract content from ANALYSIS_RESULTS.md and context-package.json
- List all detected brainstorming artifacts with correct paths

#### 3. TODO_LIST.md
**Location**: .workflow/{session-id}/TODO_LIST.md
**Structure**:
\`\`\`markdown
# Tasks: {Session Topic}

## Task Progress
▸ **IMPL-001**: [Main Task Group] → [📋](./.task/IMPL-001.json)
  - [ ] **IMPL-001.1**: [Subtask] → [📋](./.task/IMPL-001.1.json)
  - [ ] **IMPL-001.2**: [Subtask] → [📋](./.task/IMPL-001.2.json)

- [ ] **IMPL-002**: [Simple Task] → [📋](./.task/IMPL-002.json)

## Status Legend
- \`▸\` = Container task (has subtasks)
- \`- [ ]\` = Pending leaf task
- \`- [x]\` = Completed leaf task
\`\`\`

### Execution Instructions for Agent

**Agent Task**: Generate task JSON files, IMPL_PLAN.md, and TODO_LIST.md based on analysis results

**Note**: The correct task JSON template path has been pre-selected by the command based on the `--cli-execute` flag and is provided in the context as `{template_path}`.

**Step 1: Load Task JSON Template**
- Read template from the provided path: `Read({template_path})`
- This template is already the correct one based on execution mode

**Step 2: Extract and Decompose Tasks**
- Parse ANALYSIS_RESULTS.md for task recommendations
- Apply task merging rules (merge when possible, decompose only when necessary)
- Map artifacts to tasks based on domain (UI/Backend/Data)
- Ensure task count ≤10

**Step 3: Generate Task JSON Files**
- Use the template structure from Step 1
- Create .task/IMPL-*.json files with proper structure
- Replace all {placeholder} variables with actual session paths
- Embed artifacts array with brainstorming outputs
- Include MCP tool integration in pre_analysis steps

**Step 4: Create IMPL_PLAN.md**
- Use IMPL_PLAN template
- Populate all sections with session-specific content
- List artifacts with priorities and usage guidelines
- Document execution strategy and dependencies

**Step 5: Generate TODO_LIST.md**
- Create task progress checklist matching generated JSONs
- Use proper status indicators (▸, [ ], [x])
- Link to task JSON files

**Step 6: Update Session State**
- Update workflow-session.json with task count and artifact inventory
- Mark session ready for execution

### MCP Enhancement Examples

**Code Index Usage**:
\`\`\`javascript
// Discover authentication-related files
mcp__code-index__find_files(pattern="*auth*")

// Search for OAuth patterns
mcp__code-index__search_code_advanced(
  pattern="oauth|jwt|authentication",
  file_pattern="*.{ts,js}"
)

// Get file summary for key components
mcp__code-index__get_file_summary(
  file_path="src/auth/index.ts"
)
\`\`\`

**Exa Research Usage**:
\`\`\`javascript
// Get best practices for task implementation
mcp__exa__get_code_context_exa(
  query="TypeScript OAuth2 implementation patterns",
  tokensNum="dynamic"
)

// Research specific API usage
mcp__exa__get_code_context_exa(
  query="Express.js JWT middleware examples",
  tokensNum=5000
)
\`\`\`

### Quality Validation

Before completion, verify:
- [ ] All task JSON files created in .task/ directory
- [ ] Each task JSON has 5 required fields
- [ ] Artifact references correctly mapped
- [ ] Flow control includes artifact loading steps
- [ ] MCP tool integration added where appropriate
- [ ] IMPL_PLAN.md follows required structure
- [ ] TODO_LIST.md matches task JSONs
- [ ] Dependency graph is acyclic
- [ ] Task count within limits (≤10)
- [ ] Session state updated

## Output

Generate all three documents and report completion status:
- Task JSON files created: N files
- Artifacts integrated: synthesis-spec, guidance-specification, N role analyses
- MCP enhancements: code-index, exa-research
- Session ready for execution: /workflow:execute
`
)

Agent Context Passing

Memory-Aware Context Assembly:

// Assemble context package for agent
const agentContext = {
  session_id: "WFS-[id]",

  // Use memory if available, else load
  session_metadata: memory.has("workflow-session.json")
    ? memory.get("workflow-session.json")
    : Read(.workflow/WFS-[id]/workflow-session.json),

  analysis_results: memory.has("ANALYSIS_RESULTS.md")
    ? memory.get("ANALYSIS_RESULTS.md")
    : Read(.workflow/WFS-[id]/.process/ANALYSIS_RESULTS.md),

  artifacts_inventory: memory.has("artifacts_inventory")
    ? memory.get("artifacts_inventory")
    : discoverArtifacts(),

  context_package: memory.has("context-package.json")
    ? memory.get("context-package.json")
    : Read(.workflow/WFS-[id]/.process/context-package.json),

  // Optional MCP enhancements
  mcp_analysis: executeMcpDiscovery()
}