- Introduced comprehensive guidelines for generating implementation plan documents (IMPL_PLAN.md, task JSONs, TODO_LIST.md) using the action-planning-agent. - Defined auto mode for user configuration with default settings. - Outlined core philosophy emphasizing planning only, agent-driven document generation, and memory-first context loading. - Detailed execution process divided into phases: User Configuration, Context Preparation, Single Agent Planning, N Parallel Planning, and Integration. - Included lifecycle management for user configuration and agent interactions. - Specified document generation lifecycle with clear expectations for outputs and quality standards.
25 KiB
Phase 3: Conflict Resolution
Detect and resolve conflicts between plan and existing codebase using CLI-powered analysis with Gemini/Qwen.
Objective
- Analyze conflicts between plan and existing code, including module scenario uniqueness detection
- Generate multiple resolution strategies with iterative clarification until boundaries are clear
- Apply selected modifications to brainstorm artifacts
Scope: Detection and strategy generation only - NO code modification or task creation.
Trigger: Auto-executes when conflict_risk >= medium.
Auto Mode
When --yes or -y: Auto-select recommended strategy for each conflict, skip clarification questions.
Core Responsibilities
| Responsibility | Description |
|---|---|
| Detect Conflicts | Analyze plan vs existing code inconsistencies |
| Scenario Uniqueness | Search and compare new modules with existing modules for functional overlaps |
| Generate Strategies | Provide 2-4 resolution options per conflict |
| Iterative Clarification | Ask unlimited questions until scenario boundaries are clear and unique |
| Agent Re-analysis | Dynamically update strategies based on user clarifications |
| CLI Analysis | Use Gemini/Qwen (Claude fallback) |
| User Decision | Present options ONE BY ONE, never auto-apply |
| Direct Text Output | Output questions via text directly, NEVER use bash echo/printf |
| Structured Data | JSON output for programmatic processing, NO file generation |
| Explicit Lifecycle | Manage agent lifecycle with spawn_agent → wait → send_input → close_agent |
Conflict Categories
1. Architecture Conflicts
- Incompatible design patterns
- Module structure changes
- Pattern migration requirements
2. API Conflicts
- Breaking contract changes
- Signature modifications
- Public interface impacts
3. Data Model Conflicts
- Schema modifications
- Type breaking changes
- Data migration needs
4. Dependency Conflicts
- Version incompatibilities
- Setup conflicts
- Breaking updates
5. Module Scenario Overlap
- Functional overlap between new and existing modules
- Scenario boundary ambiguity
- Duplicate responsibility detection
- Module merge/split decisions
- Requires iterative clarification until uniqueness confirmed
Execution Process
Input Parsing:
├─ Parse flags: --session, --context
└─ Validation: Both REQUIRED, conflict_risk >= medium
Phase 1: Validation
├─ Step 1: Verify session directory exists
├─ Step 2: Load context-package.json
├─ Step 3: Check conflict_risk (skip if none/low)
└─ Step 4: Prepare agent task prompt
Phase 2: CLI-Powered Analysis (Agent with Dual Role)
├─ Spawn agent with exploration + planning capability
├─ Execute Gemini analysis (Qwen fallback)
├─ Detect conflicts including ModuleOverlap category
└─ Generate 2-4 strategies per conflict with modifications
Phase 3: Iterative User Interaction (using send_input)
└─ FOR each conflict (one by one):
├─ Display conflict with overlap_analysis (if ModuleOverlap)
├─ Display strategies (2-4 + custom option)
├─ User selects strategy
└─ IF clarification_needed:
├─ Collect answers
├─ send_input for agent re-analysis
└─ Loop until uniqueness_confirmed (max 10 rounds)
Phase 4: Apply Modifications
├─ Step 1: Extract modifications from resolved strategies
├─ Step 2: Apply using Edit tool
├─ Step 3: Update context-package.json (mark resolved)
├─ Step 4: Close agent
└─ Step 5: Output custom conflict summary (if any)
Execution Flow
Phase 1: Validation
1. Verify session directory exists
2. Load context-package.json
3. Check conflict_risk (skip if none/low)
4. Prepare agent task prompt
Phase 2: CLI-Powered Analysis
Agent Delegation with Dual Role (enables multi-round interaction):
// Spawn agent with combined analysis + resolution capability
const conflictAgentId = spawn_agent({
message: `
## TASK ASSIGNMENT
### MANDATORY FIRST STEPS (Agent Execute)
1. **Read role definition**: ~/.codex/agents/cli-execution-agent.md (MUST read first)
2. Read: .workflow/project-tech.json
3. Read: .workflow/project-guidelines.json
---
## Context
- Session: ${session_id}
- Risk: ${conflict_risk}
- Files: ${existing_files_list}
## Exploration Context (from context-package.exploration_results)
- Exploration Count: ${contextPackage.exploration_results?.exploration_count || 0}
- Angles Analyzed: ${JSON.stringify(contextPackage.exploration_results?.angles || [])}
- Pre-identified Conflict Indicators: ${JSON.stringify(contextPackage.exploration_results?.aggregated_insights?.conflict_indicators || [])}
- Critical Files: ${JSON.stringify(contextPackage.exploration_results?.aggregated_insights?.critical_files?.map(f => f.path) || [])}
- All Patterns: ${JSON.stringify(contextPackage.exploration_results?.aggregated_insights?.all_patterns || [])}
- All Integration Points: ${JSON.stringify(contextPackage.exploration_results?.aggregated_insights?.all_integration_points || [])}
## Analysis Steps
### 0. Load Output Schema (MANDATORY)
Execute: cat ~/.claude/workflows/cli-templates/schemas/conflict-resolution-schema.json
### 1. Load Context
- Read existing files from conflict_detection.existing_files
- Load plan from .workflow/active/${session_id}/.process/context-package.json
- Load exploration_results and use aggregated_insights for enhanced analysis
- Extract role analyses and requirements
### 2. Execute CLI Analysis (Enhanced with Exploration + Scenario Uniqueness)
Primary (Gemini):
ccw cli -p "
PURPOSE: Detect conflicts between plan and codebase, using exploration insights
TASK:
• **Review pre-identified conflict_indicators from exploration results**
• Compare architectures (use exploration key_patterns)
• Identify breaking API changes
• Detect data model incompatibilities
• Assess dependency conflicts
• **Analyze module scenario uniqueness**
- Use exploration integration_points for precise locations
- Cross-validate with exploration critical_files
- Generate clarification questions for boundary definition
MODE: analysis
CONTEXT: @**/*.ts @**/*.js @**/*.tsx @**/*.jsx @.workflow/active/${session_id}/**/*
EXPECTED: Conflict list with severity ratings, including:
- Validation of exploration conflict_indicators
- ModuleOverlap conflicts with overlap_analysis
- Targeted clarification questions
CONSTRAINTS: Focus on breaking changes, migration needs, and functional overlaps | Prioritize exploration-identified conflicts | analysis=READ-ONLY
" --tool gemini --mode analysis --rule analysis-code-patterns --cd ${project_root}
Fallback: Qwen (same prompt) → Claude (manual analysis)
### 3. Generate Strategies (2-4 per conflict)
Template per conflict:
- Severity: Critical/High/Medium
- Category: Architecture/API/Data/Dependency/ModuleOverlap
- Affected files + impact
- **For ModuleOverlap**: Include overlap_analysis with existing modules and scenarios
- Options with pros/cons, effort, risk
- **For ModuleOverlap strategies**: Add clarification_needed questions for boundary definition
- Recommended strategy + rationale
### 4. Return Structured Conflict Data
⚠️ Output to conflict-resolution.json (generated in Phase 4)
**Schema Reference**: Execute \`cat ~/.claude/workflows/cli-templates/schemas/conflict-resolution-schema.json\` to get full schema
Return JSON following the schema above. Key requirements:
- Minimum 2 strategies per conflict, max 4
- All text in Chinese for user-facing fields (brief, name, pros, cons, modification_suggestions)
- modifications.old_content: 20-100 chars for unique Edit tool matching
- modifications.new_content: preserves markdown formatting
- modification_suggestions: 2-5 actionable suggestions for custom handling
### 5. Planning Notes Record (REQUIRED)
After analysis complete, append a brief execution record to planning-notes.md:
**File**: .workflow/active/${session_id}/planning-notes.md
**Location**: Under "## Conflict Decisions (Phase 3)" section
**Format**:
\`\`\`
### [Conflict-Resolution Agent] YYYY-MM-DD
- **Note**: [brief summary of conflict types, resolution strategies, key decisions]
\`\`\`
`
});
// Wait for initial analysis
const analysisResult = wait({
ids: [conflictAgentId],
timeout_ms: 600000 // 10 minutes
});
// Parse conflicts from result
const conflicts = parseConflictsFromResult(analysisResult);
Phase 3: User Interaction Loop
const autoYes = $ARGUMENTS.includes('--yes') || $ARGUMENTS.includes('-y')
FOR each conflict:
round = 0, clarified = false, userClarifications = []
WHILE (!clarified && round++ < 10):
// 1. Display conflict info (text output for context)
displayConflictSummary(conflict) // id, brief, severity, overlap_analysis if ModuleOverlap
// 2. Strategy selection
if (autoYes) {
console.log(`[--yes] Auto-selecting recommended strategy`)
selectedStrategy = conflict.strategies[conflict.recommended || 0]
clarified = true // Skip clarification loop
} else {
AskUserQuestion({
questions: [{
question: formatStrategiesForDisplay(conflict.strategies),
header: "策略选择",
multiSelect: false,
options: [
...conflict.strategies.map((s, i) => ({
label: `${s.name}${i === conflict.recommended ? ' (推荐)' : ''}`,
description: `${s.complexity}复杂度 | ${s.risk}风险${s.clarification_needed?.length ? ' | ⚠️需澄清' : ''}`
})),
{ label: "自定义修改", description: `建议: ${conflict.modification_suggestions?.slice(0,2).join('; ')}` }
]
}]
})
// 3. Handle selection
if (userChoice === "自定义修改") {
customConflicts.push({ id, brief, category, suggestions, overlap_analysis })
break
}
selectedStrategy = findStrategyByName(userChoice)
}
// 4. Clarification (if needed) - using send_input for agent re-analysis
if (!autoYes && selectedStrategy.clarification_needed?.length > 0) {
for (batch of chunk(selectedStrategy.clarification_needed, 4)) {
AskUserQuestion({
questions: batch.map((q, i) => ({
question: q, header: `澄清${i+1}`, multiSelect: false,
options: [{ label: "详细说明", description: "提供答案" }]
}))
})
userClarifications.push(...collectAnswers(batch))
}
// 5. Agent re-analysis via send_input (key: agent stays active)
send_input({
id: conflictAgentId,
message: `
## CLARIFICATION ANSWERS
Conflict: ${conflict.id}
Strategy: ${selectedStrategy.name}
User Clarifications: ${JSON.stringify(userClarifications)}
## REQUEST
Based on the clarifications above, update the strategy assessment.
Output: { uniqueness_confirmed: boolean, rationale: string, updated_strategy: {...}, remaining_questions: [...] }
`
});
// Wait for re-analysis result
const reanalysisResult = wait({
ids: [conflictAgentId],
timeout_ms: 300000 // 5 minutes
});
const parsedResult = parseReanalysisResult(reanalysisResult);
if (parsedResult.uniqueness_confirmed) {
selectedStrategy = { ...parsedResult.updated_strategy, clarifications: userClarifications }
clarified = true
} else {
selectedStrategy.clarification_needed = parsedResult.remaining_questions
}
} else {
clarified = true
}
if (clarified) resolvedConflicts.push({ conflict, strategy: selectedStrategy })
END WHILE
END FOR
selectedStrategies = resolvedConflicts.map(r => ({
conflict_id: r.conflict.id, strategy: r.strategy, clarifications: r.strategy.clarifications || []
}))
Key Points:
- AskUserQuestion: max 4 questions/call, batch if more
- Strategy options: 2-4 strategies + "自定义修改"
- Clarification loop via send_input: max 10 rounds, agent判断 uniqueness_confirmed
- Agent stays active throughout interaction (no close_agent until Phase 4 complete)
- Custom conflicts: 记录 overlap_analysis 供后续手动处理
Phase 4: Apply Modifications
// 1. Extract modifications from resolved strategies
const modifications = [];
selectedStrategies.forEach(item => {
if (item.strategy && item.strategy.modifications) {
modifications.push(...item.strategy.modifications.map(mod => ({
...mod,
conflict_id: item.conflict_id,
clarifications: item.clarifications
})));
}
});
console.log(`\n正在应用 ${modifications.length} 个修改...`);
// 2. Apply each modification using Edit tool (with fallback to context-package.json)
const appliedModifications = [];
const failedModifications = [];
const fallbackConstraints = []; // For files that don't exist
modifications.forEach((mod, idx) => {
try {
console.log(`[${idx + 1}/${modifications.length}] 修改 ${mod.file}...`);
// Check if target file exists (brainstorm files may not exist in lite workflow)
if (!file_exists(mod.file)) {
console.log(` ⚠️ 文件不存在,写入 context-package.json 作为约束`);
fallbackConstraints.push({
source: "conflict-resolution",
conflict_id: mod.conflict_id,
target_file: mod.file,
section: mod.section,
change_type: mod.change_type,
content: mod.new_content,
rationale: mod.rationale
});
return; // Skip to next modification
}
if (mod.change_type === "update") {
Edit({
file_path: mod.file,
old_string: mod.old_content,
new_string: mod.new_content
});
} else if (mod.change_type === "add") {
// Handle addition - append or insert based on section
const fileContent = Read(mod.file);
const updated = insertContentAfterSection(fileContent, mod.section, mod.new_content);
Write(mod.file, updated);
} else if (mod.change_type === "remove") {
Edit({
file_path: mod.file,
old_string: mod.old_content,
new_string: ""
});
}
appliedModifications.push(mod);
console.log(` ✓ 成功`);
} catch (error) {
console.log(` ✗ 失败: ${error.message}`);
failedModifications.push({ ...mod, error: error.message });
}
});
// 2b. Generate conflict-resolution.json output file
const resolutionOutput = {
session_id: sessionId,
resolved_at: new Date().toISOString(),
summary: {
total_conflicts: conflicts.length,
resolved_with_strategy: selectedStrategies.length,
custom_handling: customConflicts.length,
fallback_constraints: fallbackConstraints.length
},
resolved_conflicts: selectedStrategies.map(s => ({
conflict_id: s.conflict_id,
strategy_name: s.strategy.name,
strategy_approach: s.strategy.approach,
clarifications: s.clarifications || [],
modifications_applied: s.strategy.modifications?.filter(m =>
appliedModifications.some(am => am.conflict_id === s.conflict_id)
) || []
})),
custom_conflicts: customConflicts.map(c => ({
id: c.id,
brief: c.brief,
category: c.category,
suggestions: c.suggestions,
overlap_analysis: c.overlap_analysis || null
})),
planning_constraints: fallbackConstraints, // Constraints for files that don't exist
failed_modifications: failedModifications
};
const resolutionPath = `.workflow/active/${sessionId}/.process/conflict-resolution.json`;
Write(resolutionPath, JSON.stringify(resolutionOutput, null, 2));
// 3. Update context-package.json with resolution details (reference to JSON file)
const contextPackage = JSON.parse(Read(contextPath));
contextPackage.conflict_detection.conflict_risk = "resolved";
contextPackage.conflict_detection.resolution_file = resolutionPath; // Reference to detailed JSON
contextPackage.conflict_detection.resolved_conflicts = selectedStrategies.map(s => s.conflict_id);
contextPackage.conflict_detection.custom_conflicts = customConflicts.map(c => c.id);
contextPackage.conflict_detection.resolved_at = new Date().toISOString();
Write(contextPath, JSON.stringify(contextPackage, null, 2));
// 4. Close the conflict agent (IMPORTANT: explicit lifecycle management)
close_agent({ id: conflictAgentId });
// 5. Output custom conflict summary with overlap analysis (if any)
if (customConflicts.length > 0) {
console.log(`\n${'='.repeat(60)}`);
console.log(`需要自定义处理的冲突 (${customConflicts.length})`);
console.log(`${'='.repeat(60)}\n`);
customConflicts.forEach(conflict => {
console.log(`【${conflict.category}】${conflict.id}: ${conflict.brief}`);
// Show overlap analysis for ModuleOverlap conflicts
if (conflict.category === 'ModuleOverlap' && conflict.overlap_analysis) {
console.log(`\n场景重叠信息:`);
console.log(` 新模块: ${conflict.overlap_analysis.new_module.name}`);
console.log(` 场景: ${conflict.overlap_analysis.new_module.scenarios.join(', ')}`);
console.log(`\n 与以下模块重叠:`);
conflict.overlap_analysis.existing_modules.forEach(mod => {
console.log(` - ${mod.name} (${mod.file})`);
console.log(` 重叠场景: ${mod.overlap_scenarios.join(', ')}`);
});
}
console.log(`\n修改建议:`);
conflict.suggestions.forEach(suggestion => {
console.log(` - ${suggestion}`);
});
console.log();
});
}
// 6. Output failure summary (if any)
if (failedModifications.length > 0) {
console.log(`\n⚠️ 部分修改失败 (${failedModifications.length}):`);
failedModifications.forEach(mod => {
console.log(` - ${mod.file}: ${mod.error}`);
});
}
// 7. Return summary
return {
total_conflicts: conflicts.length,
resolved_with_strategy: selectedStrategies.length,
custom_handling: customConflicts.length,
modifications_applied: appliedModifications.length,
modifications_failed: failedModifications.length,
modified_files: [...new Set(appliedModifications.map(m => m.file))],
custom_conflicts: customConflicts,
clarification_records: selectedStrategies.filter(s => s.clarifications.length > 0)
};
Validation:
✓ Agent returns valid JSON structure with ModuleOverlap conflicts
✓ Conflicts processed ONE BY ONE (not in batches)
✓ ModuleOverlap conflicts include overlap_analysis field
✓ Strategies with clarification_needed display questions
✓ User selections captured correctly per conflict
✓ Clarification loop continues until uniqueness confirmed via send_input
✓ Agent re-analysis with user clarifications updates strategy
✓ Uniqueness confirmation based on clear scenario boundaries
✓ Maximum 10 rounds per conflict safety limit enforced
✓ Edit tool successfully applies modifications
✓ guidance-specification.md updated
✓ Role analyses (*.md) updated
✓ context-package.json marked as resolved with clarification records
✓ Custom conflicts display overlap_analysis for manual handling
✓ Agent closed after all interactions complete (explicit lifecycle)
✓ Agent log saved to .workflow/active/{session_id}/.chat/
Output Format
Primary Output: conflict-resolution.json
Path: .workflow/active/{session_id}/.process/conflict-resolution.json
Schema:
{
"session_id": "WFS-xxx",
"resolved_at": "ISO timestamp",
"summary": {
"total_conflicts": 3,
"resolved_with_strategy": 2,
"custom_handling": 1,
"fallback_constraints": 0
},
"resolved_conflicts": [
{
"conflict_id": "CON-001",
"strategy_name": "策略名称",
"strategy_approach": "实现方法",
"clarifications": [],
"modifications_applied": []
}
],
"custom_conflicts": [
{
"id": "CON-002",
"brief": "冲突摘要",
"category": "ModuleOverlap",
"suggestions": ["建议1", "建议2"],
"overlap_analysis": null
}
],
"planning_constraints": [],
"failed_modifications": []
}
Key Requirements
| Requirement | Details |
|---|---|
| Conflict batching | Max 10 conflicts per round (no total limit) |
| Strategy count | 2-4 strategies per conflict |
| Modifications | Each strategy includes file paths, old_content, new_content |
| User-facing text | Chinese (brief, strategy names, pros/cons) |
| Technical fields | English (severity, category, complexity, risk) |
| old_content precision | 20-100 chars for unique Edit tool matching |
| File targets | guidance-specification.md, role analyses (*.md) |
| Agent lifecycle | Keep active during interaction, close after Phase 4 |
Error Handling
Recovery Strategy
1. Pre-check: Verify conflict_risk ≥ medium
2. Monitor: Track agent via wait with timeout
3. Validate: Parse agent JSON output
4. Recover:
- Agent failure → check logs + report error
- Invalid JSON → retry once with Claude fallback
- CLI failure → fallback to Claude analysis
- Edit tool failure → report affected files + rollback option
- User cancels → mark as "unresolved", continue to task-generate
5. Degrade: If all fail, generate minimal conflict report and skip modifications
6. Cleanup: Always close_agent even on error path
Rollback Handling
If Edit tool fails mid-application:
1. Log all successfully applied modifications
2. Output rollback option via text interaction
3. If rollback selected: restore files from git or backups
4. If continue: mark partial resolution in context-package.json
Integration
Interface
Input:
--session(required): WFS-{session-id}--context(required): context-package.json path- Requires:
conflict_risk >= medium
Output:
- Generated file:
.workflow/active/{session_id}/.process/conflict-resolution.json(primary output)
- Modified files (if exist):
.workflow/active/{session_id}/.brainstorm/guidance-specification.md.workflow/active/{session_id}/.brainstorm/{role}/analysis.md.workflow/active/{session_id}/.process/context-package.json(conflict_risk → resolved, resolution_file reference)
User Interaction:
- Iterative conflict processing: One conflict at a time, not in batches
- Each conflict: 2-4 strategy options + "自定义修改" option (with suggestions)
- Clarification loop via send_input: Unlimited questions per conflict until uniqueness confirmed (max 10 rounds)
- ModuleOverlap conflicts: Display overlap_analysis with existing modules
- Agent re-analysis: Dynamic strategy updates based on user clarifications
Success Criteria
✓ CLI analysis returns valid JSON structure with ModuleOverlap category
✓ Agent performs scenario uniqueness detection (searches existing modules)
✓ Conflicts processed ONE BY ONE with iterative clarification via send_input
✓ Min 2 strategies per conflict with modifications
✓ ModuleOverlap conflicts include overlap_analysis with existing modules
✓ Strategies requiring clarification include clarification_needed questions
✓ Each conflict includes 2-5 modification_suggestions
✓ Text output displays conflict with overlap analysis (if ModuleOverlap)
✓ User selections captured per conflict
✓ Clarification loop continues until uniqueness confirmed (unlimited rounds, max 10)
✓ Agent re-analysis with user clarifications updates strategy
✓ Uniqueness confirmation based on clear scenario boundaries
✓ Edit tool applies modifications successfully
✓ Custom conflicts displayed with overlap_analysis for manual handling
✓ guidance-specification.md updated with resolved conflicts
✓ Role analyses (*.md) updated with resolved conflicts
✓ context-package.json marked as "resolved" with clarification records
✓ conflict-resolution.json generated with full resolution details
✓ Agent explicitly closed after all interactions
✓ Modification summary includes:
- Total conflicts
- Resolved with strategy (count)
- Custom handling (count)
- Clarification records
- Overlap analysis for custom ModuleOverlap conflicts
✓ Agent log saved to .workflow/active/{session_id}/.chat/
✓ Error handling robust (validate/retry/degrade)
Post-Phase Update
If Phase 3 was executed, update planning-notes.md:
const conflictResPath = `.workflow/active/${sessionId}/.process/conflict-resolution.json`
if (file_exists(conflictResPath)) {
const conflictRes = JSON.parse(Read(conflictResPath))
const resolved = conflictRes.resolved_conflicts || []
const planningConstraints = conflictRes.planning_constraints || []
// Update Phase 3 section
Edit(planningNotesPath, {
old: '## Conflict Decisions (Phase 3)\n(To be filled if conflicts detected)',
new: `## Conflict Decisions (Phase 3)
- **RESOLVED**: ${resolved.map(r => `${r.conflict_id} → ${r.strategy_name}`).join('; ') || 'None'}
- **CUSTOM_HANDLING**: ${conflictRes.custom_conflicts?.map(c => c.id).join(', ') || 'None'}
- **CONSTRAINTS**: ${planningConstraints.map(c => c.content).join('; ') || 'None'}`
})
// Append Phase 3 constraints to consolidated list
if (planningConstraints.length > 0) {
Edit(planningNotesPath, {
old: '## Consolidated Constraints (Phase 4 Input)',
new: `## Consolidated Constraints (Phase 4 Input)
${planningConstraints.map((c, i) => `${constraintCount + i + 1}. [Conflict] ${c.content}`).join('\n')}`
})
}
}
Memory State Check
After Phase 3 completion, evaluate context window usage. If memory usage is high (>120K tokens):
// Codex: Use compact command if available
codex compact
Output
- File:
.workflow/active/{sessionId}/.process/conflict-resolution.json - Modified files: brainstorm artifacts (guidance-specification.md, role analyses)
- Updated:
context-package.jsonwith resolved conflict status
Next Phase
Return to orchestrator, then auto-continue to Phase 4: Task Generation.