feat: convert lite-plan and multi-cli-plan commands to orchestrator+phases skills

Convert workflow commands to unified skill structure with thin router pattern:
- workflow-lite-plan: routes lite-plan + lite-execute with prompt enhancement
- workflow-multi-cli-plan: routes multi-cli-plan + lite-execute with prompt enhancement
Both preserve original command content verbatim in phase files.
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catlog22
2026-02-13 23:25:42 +08:00
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# Phase 1: Multi-CLI Collaborative Planning
Complete multi-CLI collaborative planning pipeline with ACE context gathering and iterative cross-verification. This phase document preserves the full content of the original `workflow:multi-cli-plan` command.
> **Source**: Converted from `.claude/commands/workflow/multi-cli-plan.md`. Frontmatter moved to SKILL.md.
## Auto Mode
When `--yes` or `-y`: Auto-approve plan, use recommended solution and execution method (Agent, Skip review).
# Multi-CLI Collaborative Planning Command
## Quick Start
```bash
# Basic usage
/workflow:multi-cli-plan "Implement user authentication"
# With options
/workflow:multi-cli-plan "Add dark mode support" --max-rounds=3
/workflow:multi-cli-plan "Refactor payment module" --tools=gemini,codex,claude
/workflow:multi-cli-plan "Fix memory leak" --mode=serial
```
**Context Source**: ACE semantic search + Multi-CLI analysis
**Output Directory**: `.workflow/.multi-cli-plan/{session-id}/`
**Default Max Rounds**: 3 (convergence may complete earlier)
**CLI Tools**: @cli-discuss-agent (analysis), @cli-lite-planning-agent (plan generation)
**Execution**: Auto-hands off to `/workflow:lite-execute --in-memory` after plan approval
## What & Why
### Core Concept
Multi-CLI collaborative planning with **three-phase architecture**: ACE context gathering → Iterative multi-CLI discussion → Plan generation. Orchestrator delegates analysis to agents, only handles user decisions and session management.
**Process**:
- **Phase 1**: ACE semantic search gathers codebase context
- **Phase 2**: cli-discuss-agent orchestrates Gemini/Codex/Claude for cross-verified analysis
- **Phase 3-5**: User decision → Plan generation → Execution handoff
**vs Single-CLI Planning**:
- **Single**: One model perspective, potential blind spots
- **Multi-CLI**: Cross-verification catches inconsistencies, builds consensus on solutions
### Value Proposition
1. **Multi-Perspective Analysis**: Gemini + Codex + Claude analyze from different angles
2. **Cross-Verification**: Identify agreements/disagreements, build confidence
3. **User-Driven Decisions**: Every round ends with user decision point
4. **Iterative Convergence**: Progressive refinement until consensus reached
### Orchestrator Boundary (CRITICAL)
- **ONLY command** for multi-CLI collaborative planning
- Manages: Session state, user decisions, agent delegation, phase transitions
- Delegates: CLI execution to @cli-discuss-agent, plan generation to @cli-lite-planning-agent
### Execution Flow
```
Phase 1: Context Gathering
└─ ACE semantic search, extract keywords, build context package
Phase 2: Multi-CLI Discussion (Iterative, via @cli-discuss-agent)
├─ Round N: Agent executes Gemini + Codex + Claude
├─ Cross-verify findings, synthesize solutions
├─ Write synthesis.json to rounds/{N}/
└─ Loop until convergence or max rounds
Phase 3: Present Options
└─ Display solutions with trade-offs from agent output
Phase 4: User Decision
├─ Select solution approach
├─ Select execution method (Agent/Codex/Auto)
├─ Select code review tool (Skip/Gemini/Codex/Agent)
└─ Route:
├─ Approve → Phase 5
├─ Need More Analysis → Return to Phase 2
└─ Cancel → Save session
Phase 5: Plan Generation & Execution Handoff
├─ Generate plan.json + .task/*.json (via @cli-lite-planning-agent, two-layer output)
├─ Build executionContext with user selections and taskFiles
└─ Execute to /workflow:lite-execute --in-memory
```
### Agent Roles
| Agent | Responsibility |
|-------|---------------|
| **Orchestrator** | Session management, ACE context, user decisions, phase transitions, executionContext assembly |
| **@cli-discuss-agent** | Multi-CLI execution (Gemini/Codex/Claude), cross-verification, solution synthesis, synthesis.json output |
| **@cli-lite-planning-agent** | Task decomposition, two-layer output: plan.json (overview with task_ids[]) + .task/*.json (task files) |
## Core Responsibilities
### Phase 1: Context Gathering
**Session Initialization**:
```javascript
const sessionId = `MCP-${taskSlug}-${date}`
const sessionFolder = `.workflow/.multi-cli-plan/${sessionId}`
Bash(`mkdir -p ${sessionFolder}/rounds`)
```
**ACE Context Queries**:
```javascript
const aceQueries = [
`Project architecture related to ${keywords}`,
`Existing implementations of ${keywords[0]}`,
`Code patterns for ${keywords} features`,
`Integration points for ${keywords[0]}`
]
// Execute via mcp__ace-tool__search_context
```
**Context Package** (passed to agent):
- `relevant_files[]` - Files identified by ACE
- `detected_patterns[]` - Code patterns found
- `architecture_insights` - Structure understanding
### Phase 2: Agent Delegation
**Core Principle**: Orchestrator only delegates and reads output - NO direct CLI execution.
**⚠️ CRITICAL - CLI EXECUTION REQUIREMENT**:
- **MUST** execute CLI calls via `Bash` with `run_in_background: true`
- **MUST** wait for hook callback to receive complete results
- **MUST NOT** proceed with next phase until CLI execution fully completes
- Do NOT use `TaskOutput` polling during CLI execution - wait passively for results
- Minimize scope: Proceed only when 100% result available
**Agent Invocation**:
```javascript
Task({
subagent_type: "cli-discuss-agent",
run_in_background: false,
description: `Discussion round ${currentRound}`,
prompt: `
## Input Context
- task_description: ${taskDescription}
- round_number: ${currentRound}
- session: { id: "${sessionId}", folder: "${sessionFolder}" }
- ace_context: ${JSON.stringify(contextPackageage)}
- previous_rounds: ${JSON.stringify(analysisResults)}
- user_feedback: ${userFeedback || 'None'}
- cli_config: { tools: ["gemini", "codex"], mode: "parallel", fallback_chain: ["gemini", "codex", "claude"] }
## Execution Process
1. Parse input context (handle JSON strings)
2. Check if ACE supplementary search needed
3. Build CLI prompts with context
4. Execute CLIs (parallel or serial per cli_config.mode)
5. Parse CLI outputs, handle failures with fallback
6. Perform cross-verification between CLI results
7. Synthesize solutions, calculate scores
8. Calculate convergence, generate clarification questions
9. Write synthesis.json
## Output
Write: ${sessionFolder}/rounds/${currentRound}/synthesis.json
## Completion Checklist
- [ ] All configured CLI tools executed (or fallback triggered)
- [ ] Cross-verification completed with agreements/disagreements
- [ ] 2-3 solutions generated with file:line references
- [ ] Convergence score calculated (0.0-1.0)
- [ ] synthesis.json written with all Primary Fields
`
})
```
**Read Agent Output**:
```javascript
const synthesis = JSON.parse(Read(`${sessionFolder}/rounds/${round}/synthesis.json`))
// Access top-level fields: solutions, convergence, cross_verification, clarification_questions
```
**Convergence Decision**:
```javascript
if (synthesis.convergence.recommendation === 'converged') {
// Proceed to Phase 3
} else if (synthesis.convergence.recommendation === 'user_input_needed') {
// Collect user feedback, return to Phase 2
} else {
// Continue to next round if new_insights && round < maxRounds
}
```
### Phase 3: Present Options
**Display from Agent Output** (no processing):
```javascript
console.log(`
## Solution Options
${synthesis.solutions.map((s, i) => `
**Option ${i+1}: ${s.name}**
Source: ${s.source_cli.join(' + ')}
Effort: ${s.effort} | Risk: ${s.risk}
Pros: ${s.pros.join(', ')}
Cons: ${s.cons.join(', ')}
Files: ${s.affected_files.slice(0,3).map(f => `${f.file}:${f.line}`).join(', ')}
`).join('\n')}
## Cross-Verification
Agreements: ${synthesis.cross_verification.agreements.length}
Disagreements: ${synthesis.cross_verification.disagreements.length}
`)
```
### Phase 4: User Decision
**Decision Options**:
```javascript
AskUserQuestion({
questions: [
{
question: "Which solution approach?",
header: "Solution",
multiSelect: false,
options: solutions.map((s, i) => ({
label: `Option ${i+1}: ${s.name}`,
description: `${s.effort} effort, ${s.risk} risk`
})).concat([
{ label: "Need More Analysis", description: "Return to Phase 2" }
])
},
{
question: "Execution method:",
header: "Execution",
multiSelect: false,
options: [
{ label: "Agent", description: "@code-developer agent" },
{ label: "Codex", description: "codex CLI tool" },
{ label: "Auto", description: "Auto-select based on complexity" }
]
},
{
question: "Code review after execution?",
header: "Review",
multiSelect: false,
options: [
{ label: "Skip", description: "No review" },
{ label: "Gemini Review", description: "Gemini CLI tool" },
{ label: "Codex Review", description: "codex review --uncommitted" },
{ label: "Agent Review", description: "Current agent review" }
]
}
]
})
```
**Routing**:
- Approve + execution method → Phase 5
- Need More Analysis → Phase 2 with feedback
- Cancel → Save session for resumption
### Phase 5: Plan Generation & Execution Handoff
**Step 1: Build Context-Package** (Orchestrator responsibility):
```javascript
// Extract key information from user decision and synthesis
const contextPackage = {
// Core solution details
solution: {
name: selectedSolution.name,
source_cli: selectedSolution.source_cli,
feasibility: selectedSolution.feasibility,
effort: selectedSolution.effort,
risk: selectedSolution.risk,
summary: selectedSolution.summary
},
// Implementation plan (tasks, flow, milestones)
implementation_plan: selectedSolution.implementation_plan,
// Dependencies
dependencies: selectedSolution.dependencies || { internal: [], external: [] },
// Technical concerns
technical_concerns: selectedSolution.technical_concerns || [],
// Consensus from cross-verification
consensus: {
agreements: synthesis.cross_verification.agreements,
resolved_conflicts: synthesis.cross_verification.resolution
},
// User constraints (from Phase 4 feedback)
constraints: userConstraints || [],
// Task context
task_description: taskDescription,
session_id: sessionId
}
// Write context-package for traceability
Write(`${sessionFolder}/context-package.json`, JSON.stringify(contextPackage, null, 2))
```
**Context-Package Schema**:
| Field | Type | Description |
|-------|------|-------------|
| `solution` | object | User-selected solution from synthesis |
| `solution.name` | string | Solution identifier |
| `solution.feasibility` | number | Viability score (0-1) |
| `solution.summary` | string | Brief analysis summary |
| `implementation_plan` | object | Task breakdown with flow and dependencies |
| `implementation_plan.approach` | string | High-level technical strategy |
| `implementation_plan.tasks[]` | array | Discrete tasks with id, name, depends_on, files |
| `implementation_plan.execution_flow` | string | Task sequence (e.g., "T1 → T2 → T3") |
| `implementation_plan.milestones` | string[] | Key checkpoints |
| `dependencies` | object | Module and package dependencies |
| `technical_concerns` | string[] | Risks and blockers |
| `consensus` | object | Cross-verified agreements from multi-CLI |
| `constraints` | string[] | User-specified constraints from Phase 4 |
```json
{
"solution": {
"name": "Strategy Pattern Refactoring",
"source_cli": ["gemini", "codex"],
"feasibility": 0.88,
"effort": "medium",
"risk": "low",
"summary": "Extract payment gateway interface, implement strategy pattern for multi-gateway support"
},
"implementation_plan": {
"approach": "Define interface → Create concrete strategies → Implement factory → Migrate existing code",
"tasks": [
{"id": "T1", "name": "Define PaymentGateway interface", "depends_on": [], "files": [{"file": "src/types/payment.ts", "line": 1, "action": "create"}], "key_point": "Include all existing Stripe methods"},
{"id": "T2", "name": "Implement StripeGateway", "depends_on": ["T1"], "files": [{"file": "src/payment/stripe.ts", "line": 1, "action": "create"}], "key_point": "Wrap existing logic"},
{"id": "T3", "name": "Create GatewayFactory", "depends_on": ["T1"], "files": [{"file": "src/payment/factory.ts", "line": 1, "action": "create"}], "key_point": null},
{"id": "T4", "name": "Migrate processor to use factory", "depends_on": ["T2", "T3"], "files": [{"file": "src/payment/processor.ts", "line": 45, "action": "modify"}], "key_point": "Backward compatible"}
],
"execution_flow": "T1 → (T2 | T3) → T4",
"milestones": ["Interface defined", "Gateway implementations complete", "Migration done"]
},
"dependencies": {
"internal": ["@/lib/payment-gateway", "@/types/payment"],
"external": ["stripe@^14.0.0"]
},
"technical_concerns": ["Existing tests must pass", "No breaking API changes"],
"consensus": {
"agreements": ["Use strategy pattern", "Keep existing API"],
"resolved_conflicts": "Factory over DI for simpler integration"
},
"constraints": ["backward compatible", "no breaking changes to PaymentResult type"],
"task_description": "Refactor payment processing for multi-gateway support",
"session_id": "MCP-payment-refactor-2026-01-14"
}
```
**Step 2: Invoke Planning Agent**:
```javascript
Task({
subagent_type: "cli-lite-planning-agent",
run_in_background: false,
description: "Generate implementation plan",
prompt: `
## Schema Reference
Execute: cat ~/.ccw/workflows/cli-templates/schemas/plan-overview-base-schema.json
Execute: cat ~/.ccw/workflows/cli-templates/schemas/task-schema.json
## Output Format: Two-Layer Structure
- plan.json: Overview with task_ids[] referencing .task/ files (NO tasks[] array)
- .task/TASK-*.json: Independent task files following task-schema.json
plan.json required: summary, approach, task_ids, task_count, _metadata (with plan_type)
Task files required: id, title, description, depends_on, convergence (with criteria[])
Task fields: files[].change (not modification_points), convergence.criteria (not acceptance), test (not verification)
## Context-Package (from orchestrator)
${JSON.stringify(contextPackage, null, 2)}
## Execution Process
1. Read plan-overview-base-schema.json + task-schema.json for output structure
2. Read project-tech.json and project-guidelines.json
3. Parse context-package fields:
- solution: name, feasibility, summary
- implementation_plan: tasks[], execution_flow, milestones
- dependencies: internal[], external[]
- technical_concerns: risks/blockers
- consensus: agreements, resolved_conflicts
- constraints: user requirements
4. Use implementation_plan.tasks[] as task foundation
5. Preserve task dependencies (depends_on) and execution_flow
6. Expand tasks with convergence.criteria (testable completion conditions)
7. Create .task/ directory and write individual TASK-*.json files
8. Generate plan.json with task_ids[] referencing .task/ files
## Output
- ${sessionFolder}/plan.json (overview with task_ids[])
- ${sessionFolder}/.task/TASK-*.json (independent task files)
## Completion Checklist
- [ ] plan.json has task_ids[] and task_count (NO embedded tasks[])
- [ ] .task/*.json files preserve task dependencies from implementation_plan
- [ ] Task execution order follows execution_flow
- [ ] Key_points reflected in task descriptions
- [ ] User constraints applied to implementation
- [ ] convergence.criteria are testable
- [ ] plan.json follows plan-overview-base-schema.json
- [ ] Task files follow task-schema.json
`
})
```
**Step 3: Build executionContext**:
```javascript
// After plan.json is generated by cli-lite-planning-agent
const plan = JSON.parse(Read(`${sessionFolder}/plan.json`))
// Load task files from .task/ directory (two-layer format)
const taskFiles = plan.task_ids.map(id => `${sessionFolder}/.task/${id}.json`)
// Build executionContext (same structure as lite-plan)
executionContext = {
planObject: plan,
taskFiles: taskFiles, // Paths to .task/*.json files (two-layer format)
explorationsContext: null, // Multi-CLI doesn't use exploration files
explorationAngles: [], // No exploration angles
explorationManifest: null, // No manifest
clarificationContext: null, // Store user feedback from Phase 2 if exists
executionMethod: userSelection.execution_method, // From Phase 4
codeReviewTool: userSelection.code_review_tool, // From Phase 4
originalUserInput: taskDescription,
// Optional: Task-level executor assignments
executorAssignments: null, // Could be enhanced in future
session: {
id: sessionId,
folder: sessionFolder,
artifacts: {
explorations: [], // No explorations in multi-CLI workflow
explorations_manifest: null,
plan: `${sessionFolder}/plan.json`,
task_dir: plan.task_ids ? `${sessionFolder}/.task/` : null,
synthesis_rounds: Array.from({length: currentRound}, (_, i) =>
`${sessionFolder}/rounds/${i+1}/synthesis.json`
),
context_package: `${sessionFolder}/context-package.json`
}
}
}
```
**Step 4: Hand off to Execution**:
```javascript
// Execute to lite-execute with in-memory context
Skill(skill="workflow:lite-execute", args="--in-memory")
```
## Output File Structure
```
.workflow/.multi-cli-plan/{MCP-task-slug-YYYY-MM-DD}/
├── session-state.json # Session tracking (orchestrator)
├── rounds/
│ ├── 1/synthesis.json # Round 1 analysis (cli-discuss-agent)
│ ├── 2/synthesis.json # Round 2 analysis (cli-discuss-agent)
│ └── .../
├── context-package.json # Extracted context for planning (orchestrator)
├── plan.json # Plan overview with task_ids[] (NO embedded tasks[])
└── .task/ # Independent task files
├── TASK-001.json # Task file following task-schema.json
├── TASK-002.json
└── ...
```
**File Producers**:
| File | Producer | Content |
|------|----------|---------|
| `session-state.json` | Orchestrator | Session metadata, rounds, decisions |
| `rounds/*/synthesis.json` | cli-discuss-agent | Solutions, convergence, cross-verification |
| `context-package.json` | Orchestrator | Extracted solution, dependencies, consensus for planning |
| `plan.json` | cli-lite-planning-agent | Plan overview with task_ids[] referencing .task/ files |
| `.task/*.json` | cli-lite-planning-agent | Independent task files following task-schema.json |
## synthesis.json Schema
```json
{
"round": 1,
"solutions": [{
"name": "Solution Name",
"source_cli": ["gemini", "codex"],
"feasibility": 0.85,
"effort": "low|medium|high",
"risk": "low|medium|high",
"summary": "Brief analysis summary",
"implementation_plan": {
"approach": "High-level technical approach",
"tasks": [
{"id": "T1", "name": "Task", "depends_on": [], "files": [], "key_point": "..."}
],
"execution_flow": "T1 → T2 → T3",
"milestones": ["Checkpoint 1", "Checkpoint 2"]
},
"dependencies": {"internal": [], "external": []},
"technical_concerns": ["Risk 1", "Blocker 2"]
}],
"convergence": {
"score": 0.85,
"new_insights": false,
"recommendation": "converged|continue|user_input_needed"
},
"cross_verification": {
"agreements": [],
"disagreements": [],
"resolution": "..."
},
"clarification_questions": []
}
```
**Key Planning Fields**:
| Field | Purpose |
|-------|---------|
| `feasibility` | Viability score (0-1) |
| `implementation_plan.tasks[]` | Discrete tasks with dependencies |
| `implementation_plan.execution_flow` | Task sequence visualization |
| `implementation_plan.milestones` | Key checkpoints |
| `technical_concerns` | Risks and blockers |
**Note**: Solutions ranked by internal scoring (array order = priority)
## TodoWrite Structure
**Initialization**:
```javascript
TodoWrite({ todos: [
{ content: "Phase 1: Context Gathering", status: "in_progress", activeForm: "Gathering context" },
{ content: "Phase 2: Multi-CLI Discussion", status: "pending", activeForm: "Running discussion" },
{ content: "Phase 3: Present Options", status: "pending", activeForm: "Presenting options" },
{ content: "Phase 4: User Decision", status: "pending", activeForm: "Awaiting decision" },
{ content: "Phase 5: Plan Generation", status: "pending", activeForm: "Generating plan" }
]})
```
**During Discussion Rounds**:
```javascript
TodoWrite({ todos: [
{ content: "Phase 1: Context Gathering", status: "completed", activeForm: "Gathering context" },
{ content: "Phase 2: Multi-CLI Discussion", status: "in_progress", activeForm: "Running discussion" },
{ content: " → Round 1: Initial analysis", status: "completed", activeForm: "Analyzing" },
{ content: " → Round 2: Deep verification", status: "in_progress", activeForm: "Verifying" },
{ content: "Phase 3: Present Options", status: "pending", activeForm: "Presenting options" },
// ...
]})
```
## Error Handling
| Error | Resolution |
|-------|------------|
| ACE search fails | Fall back to Glob/Grep for file discovery |
| Agent fails | Retry once, then present partial results |
| CLI timeout (in agent) | Agent uses fallback: gemini → codex → claude |
| No convergence | Present best options, flag uncertainty |
| synthesis.json parse error | Request agent retry |
| User cancels | Save session for later resumption |
## Configuration
| Flag | Default | Description |
|------|---------|-------------|
| `--max-rounds` | 3 | Maximum discussion rounds |
| `--tools` | gemini,codex | CLI tools for analysis |
| `--mode` | parallel | Execution mode: parallel or serial |
| `--auto-execute` | false | Auto-execute after approval |
## Best Practices
1. **Be Specific**: Detailed task descriptions improve ACE context quality
2. **Provide Feedback**: Use clarification rounds to refine requirements
3. **Trust Cross-Verification**: Multi-CLI consensus indicates high confidence
4. **Review Trade-offs**: Consider pros/cons before selecting solution
5. **Check synthesis.json**: Review agent output for detailed analysis
6. **Iterate When Needed**: Don't hesitate to request more analysis
## Related Commands
```bash
# Simpler single-round planning
/workflow:lite-plan "task description"
# Issue-driven discovery
/issue:discover-by-prompt "find issues"
# View session files
cat .workflow/.multi-cli-plan/{session-id}/plan.json
cat .workflow/.multi-cli-plan/{session-id}/rounds/1/synthesis.json
cat .workflow/.multi-cli-plan/{session-id}/context-package.json
# Direct execution (if you have plan.json)
/workflow:lite-execute plan.json
```
## Next Phase
Return to orchestrator, then auto-continue to [Phase 2: Lite Execute](02-lite-execute.md) via Skill handoff.