mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
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feat: 增加失败分析功能,改进问题规划和解决方案生成
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@@ -56,14 +56,61 @@ Phase 4: Validation & Output (15%)
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ccw issue status <issue-id> --json
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```
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**Step 2**: Analyze and classify
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**Step 2**: Analyze failure history (if present)
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```javascript
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function analyzeFailureHistory(issue) {
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if (!issue.feedback || issue.feedback.length === 0) {
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return { has_failures: false };
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}
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// Extract execution failures
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const failures = issue.feedback.filter(f => f.type === 'failure' && f.stage === 'execute');
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if (failures.length === 0) {
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return { has_failures: false };
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}
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// Parse failure details
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const failureAnalysis = failures.map(f => {
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const detail = JSON.parse(f.content);
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return {
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solution_id: detail.solution_id,
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task_id: detail.task_id,
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error_type: detail.error_type, // test_failure, compilation, timeout, etc.
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message: detail.message,
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stack_trace: detail.stack_trace,
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timestamp: f.created_at
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};
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});
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// Identify patterns
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const errorTypes = failureAnalysis.map(f => f.error_type);
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const repeatedErrors = errorTypes.filter((e, i, arr) => arr.indexOf(e) !== i);
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return {
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has_failures: true,
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failure_count: failures.length,
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failures: failureAnalysis,
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patterns: {
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repeated_errors: repeatedErrors, // Same error multiple times
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failed_approaches: [...new Set(failureAnalysis.map(f => f.solution_id))]
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}
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};
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}
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```
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**Step 3**: Analyze and classify
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```javascript
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function analyzeIssue(issue) {
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const failureAnalysis = analyzeFailureHistory(issue);
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return {
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issue_id: issue.id,
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requirements: extractRequirements(issue.context),
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scope: inferScope(issue.title, issue.context),
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complexity: determineComplexity(issue) // Low | Medium | High
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complexity: determineComplexity(issue), // Low | Medium | High
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failure_analysis: failureAnalysis, // Failure context for planning
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is_replan: failureAnalysis.has_failures // Flag for replanning
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}
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}
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```
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@@ -104,6 +151,41 @@ mcp__ace-tool__search_context({
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#### Phase 3: Solution Planning
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**Failure-Aware Planning** (when `issue.failure_analysis.has_failures === true`):
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```javascript
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function planWithFailureContext(issue, exploration, failureAnalysis) {
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// Identify what failed before
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const failedApproaches = failureAnalysis.patterns.failed_approaches;
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const rootCauses = failureAnalysis.failures.map(f => ({
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error: f.error_type,
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message: f.message,
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task: f.task_id
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}));
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// Design alternative approach
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const approach = `
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**Previous Attempt Analysis**:
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- Failed approaches: ${failedApproaches.join(', ')}
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- Root causes: ${rootCauses.map(r => `${r.error} (${r.task}): ${r.message}`).join('; ')}
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**Alternative Strategy**:
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- [Describe how this solution addresses root causes]
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- [Explain what's different from failed approaches]
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- [Prevention steps to catch same errors earlier]
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`;
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// Add explicit verification tasks
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const verificationTasks = rootCauses.map(rc => ({
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verification_type: rc.error,
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check: `Prevent ${rc.error}: ${rc.message}`,
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method: `Add unit test / compile check / timeout limit`
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}));
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return { approach, verificationTasks };
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}
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```
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**Multi-Solution Generation**:
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Generate multiple candidate solutions when:
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@@ -303,15 +385,17 @@ Each line is a solution JSON containing tasks. Schema: `cat .claude/workflows/cl
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**ALWAYS**:
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1. **Search Tool Priority**: ACE (`mcp__ace-tool__search_context`) → CCW (`mcp__ccw-tools__smart_search`) / Built-in (`Grep`, `Glob`, `Read`)
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2. Read schema first: `cat .claude/workflows/cli-templates/schemas/solution-schema.json`
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2. Use ACE semantic search as PRIMARY exploration tool
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3. Fetch issue details via `ccw issue status <id> --json`
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4. Quantify acceptance.criteria with testable conditions
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5. Validate DAG before output
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6. Evaluate each solution with `analysis` and `score`
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7. Write solutions to `.workflow/issues/solutions/{issue-id}.jsonl` (append mode)
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8. For HIGH complexity: generate 2-3 candidate solutions
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9. **Solution ID format**: `SOL-{issue-id}-{uid}` where uid is 4 random alphanumeric chars (e.g., `SOL-GH-123-a7x9`)
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10. **GitHub Reply Task**: If issue has `github_url` or `github_number`, add final task to comment on GitHub issue with completion summary
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3. Use ACE semantic search as PRIMARY exploration tool
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4. Fetch issue details via `ccw issue status <id> --json`
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5. **Analyze failure history**: Check `issue.feedback` for type='failure', stage='execute'
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6. **For replanning**: Reference previous failures in `solution.approach`, add prevention steps
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7. Quantify acceptance.criteria with testable conditions
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8. Validate DAG before output
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9. Evaluate each solution with `analysis` and `score`
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10. Write solutions to `.workflow/issues/solutions/{issue-id}.jsonl` (append mode)
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11. For HIGH complexity: generate 2-3 candidate solutions
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12. **Solution ID format**: `SOL-{issue-id}-{uid}` where uid is 4 random alphanumeric chars (e.g., `SOL-GH-123-a7x9`)
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13. **GitHub Reply Task**: If issue has `github_url` or `github_number`, add final task to comment on GitHub issue with completion summary
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**CONFLICT AVOIDANCE** (for batch processing of similar issues):
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1. **File isolation**: Each issue's solution should target distinct files when possible
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@@ -195,12 +195,26 @@ ${issueList}
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### Workflow
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1. Fetch issue details: ccw issue status <id> --json
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2. Load project context files
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3. Explore codebase (ACE semantic search)
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4. Plan solution with tasks (schema: solution-schema.json)
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5. **If github_url exists**: Add final task to comment on GitHub issue
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6. Write solution to: .workflow/issues/solutions/{issue-id}.jsonl
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7. Single solution → auto-bind; Multiple → return for selection
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2. **Analyze failure history** (if issue.feedback exists):
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- Extract failure details from issue.feedback (type='failure', stage='execute')
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- Parse error_type, message, task_id, solution_id from content JSON
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- Identify failure patterns: repeated errors, root causes, blockers
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- **Constraint**: Avoid repeating failed approaches
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3. Load project context files
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4. Explore codebase (ACE semantic search)
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5. Plan solution with tasks (schema: solution-schema.json)
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- **If previous solution failed**: Reference failure analysis in solution.approach
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- Add explicit verification steps to prevent same failure mode
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6. **If github_url exists**: Add final task to comment on GitHub issue
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7. Write solution to: .workflow/issues/solutions/{issue-id}.jsonl
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8. Single solution → auto-bind; Multiple → return for selection
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### Failure-Aware Planning Rules
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- **Extract failure patterns**: Parse issue.feedback where type='failure' and stage='execute'
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- **Identify root causes**: Analyze error_type (test_failure, compilation, timeout, etc.)
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- **Design alternative approach**: Create solution that addresses root cause
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- **Add prevention steps**: Include explicit verification to catch same error earlier
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- **Document lessons**: Reference previous failures in solution.approach
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### Rules
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- Solution ID format: SOL-{issue-id}-{uid} (uid: 4 random alphanumeric chars, e.g., a7x9)
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@@ -65,6 +65,35 @@
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"items": { "type": "string" },
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"description": "Files/modules affected"
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},
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"feedback": {
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"type": "array",
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"description": "Execution feedback history (failures, clarifications, rejections) for planning phase reference",
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"items": {
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"type": "object",
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"required": ["type", "stage", "content", "created_at"],
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"properties": {
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"type": {
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"type": "string",
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"enum": ["failure", "clarification", "rejection"],
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"description": "Type of feedback"
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},
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"stage": {
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"type": "string",
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"enum": ["new", "plan", "execute"],
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"description": "Which stage the feedback occurred (new=creation, plan=planning, execute=execution)"
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},
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"content": {
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"type": "string",
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"description": "JSON string for failures (with solution_id, task_id, error_type, message, stack_trace) or plain text for clarifications/rejections"
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},
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"created_at": {
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"type": "string",
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"format": "date-time",
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"description": "Timestamp when feedback was created"
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}
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}
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}
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},
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"lifecycle_requirements": {
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"type": "object",
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"properties": {
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