workflow-multi-cli-plan
Multi-CLI Collaborative Planning
Auto Mode
When workflowPreferences.autoYes is true: Auto-approve plan, use recommended solution and execution method (Agent, Skip review).
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 after plan approval
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 via workflow-lite-execute
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:
const sessionId = `MCP-${taskSlug}-${date}`
const sessionFolder = `.workflow/.multi-cli-plan/${sessionId}`
Bash(`mkdir -p ${sessionFolder}/rounds`)
ACE Context Queries:
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 ACEdetected_patterns[]- Code patterns foundarchitecture_insights- Structure understanding
Phase 2: Agent Delegation
Core Principle: Orchestrator only delegates and reads output — NO direct CLI execution. CLI calls MUST use Bash with run_in_background: true, wait for hook callback, do NOT use TaskOutput polling.
Agent Invocation:
Agent({
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(contextPackage)}
- 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:
const synthesis = JSON.parse(Read(`${sessionFolder}/rounds/${round}/synthesis.json`))
// Access top-level fields: solutions, convergence, cross_verification, clarification_questions
Convergence Decision:
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 solutions from synthesis.solutions[] showing: name, source CLIs, effort/risk, pros/cons, affected files (file:line). Also show cross-verification agreements/disagreements count.
Phase 4: User Decision
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, ${s.risk} risk`
})).concat([
{ label: "Need More Analysis", description: "Return to Phase 2" }
])
},
{
question: "Execution method:",
header: "Execution",
multiSelect: false,
options: [
{ label: "Agent", description: "@code-developer agent" },
{ label: "Codex", description: "codex CLI tool" },
{ label: "Auto", description: "Auto-select based on complexity" }
]
},
{
question: "Code review after execution?",
header: "Review",
multiSelect: false,
options: [
{ label: "Skip", description: "No review" },
{ label: "Gemini Review", description: "Gemini CLI tool" },
{ label: "Codex Review", description: "codex review --uncommitted" },
{ label: "Agent Review", description: "Current agent review" }
]
}
]
})
Routing:
- Approve + execution method → Phase 5
- Need More Analysis → Phase 2 with feedback
- Cancel → Save session for resumption
TodoWrite Update (Phase 4 Decision):
const executionLabel = userSelection.execution_method // "Agent" / "Codex" / "Auto"
TodoWrite({ todos: [
{ content: "Phase 1: Context Gathering", status: "completed", activeForm: "Gathering context" },
{ content: "Phase 2: Multi-CLI Discussion", status: "completed", activeForm: "Running discussion" },
{ content: "Phase 3: Present Options", status: "completed", activeForm: "Presenting options" },
{ content: `Phase 4: User Decision [${executionLabel}]`, status: "completed", activeForm: "Decision recorded" },
{ content: `Phase 5: Plan Generation [${executionLabel}]`, status: "in_progress", activeForm: `Generating plan [${executionLabel}]` }
]})
Phase 5: Plan Generation & Execution Handoff
Step 1: Build Context-Package (Orchestrator responsibility):
const contextPackage = {
solution: {
name: selectedSolution.name,
source_cli: selectedSolution.source_cli,
feasibility: selectedSolution.feasibility,
effort: selectedSolution.effort,
risk: selectedSolution.risk,
summary: selectedSolution.summary
},
implementation_plan: selectedSolution.implementation_plan,
dependencies: selectedSolution.dependencies || { internal: [], external: [] },
technical_concerns: selectedSolution.technical_concerns || [],
consensus: {
agreements: synthesis.cross_verification.agreements,
resolved_conflicts: synthesis.cross_verification.resolution
},
constraints: userConstraints || [],
task_description: taskDescription,
session_id: sessionId
}
Write(`${sessionFolder}/context-package.json`, JSON.stringify(contextPackage, null, 2))
Step 2: Invoke Planning Agent:
Agent({
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 specs/*.md
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[])
- ${sessionFolder}/.task/TASK-*.json (independent task files)
## Completion Checklist
- [ ] plan.json has task_ids[] and task_count (NO embedded tasks[])
- [ ] .task/*.json files preserve task dependencies from implementation_plan
- [ ] Task execution order follows execution_flow
- [ ] Key_points reflected in task descriptions
- [ ] User constraints applied to implementation
- [ ] convergence.criteria are testable
- [ ] plan.json follows plan-overview-base-schema.json
- [ ] Task files follow task-schema.json
`
})
Step 3: Build executionContext:
const plan = JSON.parse(Read(`${sessionFolder}/plan.json`))
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: [],
explorationManifest: null,
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,
executorAssignments: null,
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:
Skill({
skill: "workflow-lite-execute",
args: "--in-memory"
})
// executionContext is passed via global variable to workflow-lite-execute (Mode 1: In-Memory Plan)
synthesis.json Schema
{
"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": []
}
TodoWrite Pattern
Initialization (Phase 1 start):
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" }
]})
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
└── ...
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 |
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