Line 41518: {e}\\\", file=sys.stderr)\\n sys.exit(1)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\nEOF\\nchmod +x /home/runner/work/gh-aw/gh-aw/collect_workflow_stats.py\\necho \\\"Script created successfully\\\"\",\"description\":\"Create workflow statistics collection script\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"command\":\"cat \\u003e /home/runner/work/gh-aw/gh-aw/collect_workflow_stats.py \\u003c\\u003c 'EOF'\\n...)

Line 41415: {e}\\\", file=sys.stderr)\\n sys.exit(1)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\",\"path\":\"/home/runner/work/gh-aw/gh-aw/collect_workflow_stats.py\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"file_text\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nCollect workflow run statistics for githubnext/gh...)

Line 25619: {response.text}\\\")\\nexcept Exception as e:\\n print(f\\\"Exception: {e}\\\")\\n\\nEOF\\n\",\"description\":\"Test GitHub API access for PRs\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"command\":\"python3 << 'EOF'\\nimport json\\nimport requests\\nfrom datetime import datetime, timedelta...)

Line 22530: {result.stderr}\\\")\\n \\nexcept Exception as e:\\n print(f\\\"Exception: {e}\\\")\\nEOF\\n\",\"description\":\"Fetch recent PRs from gh-aw repo\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"command\":\"python3 << 'EOF'\\nimport json\\nimport subprocess\\nfrom datetime import datetime, timedel...)

Line 18993: {response.text}\\\")\\n all_prs = []\\n\\nEOF\\n\",\"description\":\"Test GitHub API access\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"command\":\"python3 << 'EOF'\\nimport json\\nimport requests\\nfrom datetime import datetime, timedelta...)

Line 17358: {e.stderr}\\\", file=sys.stderr)\\n return None\\n except json.JSONDecodeError as e:\\n print(f\\\"Error parsing JSON from command: {cmd}\\\", file=sys.stderr)\\n print(f\\\"Error: {e}\\\", file=sys.stderr)\\n return None\\n\\ndef calculate_stats(runs, start_date):\\n \\\"\\\"\\\"Calculate statistics for workflow runs\\\"\\\"\\\"\\n # Filter runs from past 14 days\\n filtered_runs = [\\n run for run in runs\\n if datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00')) \\u003e= start_date\\n ]\\n \\n total_runs = len(filtered_runs)\\n if total_runs == 0:\\n return {\\n 'total_runs': 0,\\n 'successful_runs': 0,\\n 'failed_runs': 0,\\n 'success_rate': 0.0,\\n 'average_duration_seconds': 0.0\\n }\\n \\n successful_runs = sum(1 for run in filtered_runs if run.get('conclusion') == 'success')\\n failed_runs = sum(1 for run in filtered_runs if run.get('conclusion') == 'failure')\\n \\n # Calculate average duration (in milliseconds from API, convert to seconds)\\n durations = [run.get('duration', 0) for run in filtered_runs if run.get('duration')]\\n avg_duration = sum(durations) / len(durations) / 1000.0 if durations else 0.0\\n \\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n return {\\n 'total_runs': total_runs,\\n 'successful_runs': successful_runs,\\n 'failed_runs': failed_runs,\\n 'success_rate': round(success_rate, 2),\\n 'average_duration_seconds': round(avg_duration, 2)\\n }\\n\\ndef main():\\n # Set up dates\\n end_date = datetime.now(timezone.utc)\\n start_date = end_date - timedelta(days=14)\\n \\n print(\\\"Fetching workflows...\\\", file=sys.stderr)\\n \\n # Get all workflows\\n workflows_data = run_gh_command(\\n \\\"gh workflow list --repo githubnext/gh-aw --json id,name,path --limit 1000\\\"\\n )\\n \\n if not workflows_data:\\n print(\\\"Failed to fetch workflows\\\", file=sys.stderr)\\n sys.exit(1)\\n \\n # Filter for .lock.yml workflows\\n lock_workflows = [w for w in workflows_data if w['path'].endswith('.lock.yml')]\\n \\n print(f\\\"Found {len(lock_workflows)} agentic workflows (.lock.yml)\\\", file=sys.stderr)\\n \\n workflow_stats = []\\n \\n for i, workflow in enumerate(lock_workflows, 1):\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"[{i}/{len(lock_workflows)}] Processing: {workflow_name}\\\", file=sys.stderr)\\n \\n # Get runs for this workflow\\n runs = run_gh_command(\\n f\\\"gh run list --repo githubnext/gh-aw --workflow {workflow_id} \\\"\\n f\\\"--limit 100 --json conclusion,duration,status,createdAt\\\"\\n )\\n \\n if runs is None:\\n print(f\\\" Warning: Failed to fetch runs for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Calculate stats\\n stats = calculate_stats(runs, start_date)\\n \\n workflow_stats.append({\\n 'workflow_name': workflow_name,\\n 'workflow_path': workflow_path,\\n 'workflow_id': workflow_id,\\n **stats\\n })\\n \\n print(f\\\" Total: {stats['total_runs']}, Success: {stats['successful_runs']}, \\\"\\n f\\\"Failed: {stats['failed_runs']}, Rate: {stats['success_rate']}%\\\", file=sys.stderr)\\n \\n # Build final output\\n output = {\\n 'metadata': {\\n 'owner': 'githubnext',\\n 'repo': 'gh-aw',\\n 'data_collection_date': end_date.isoformat(),\\n 'period_days': 14,\\n 'start_date': start_date.isoformat(),\\n 'end_date': end_date.isoformat(),\\n 'workflow_count': len(workflow_stats)\\n },\\n 'workflows': sor

Line 14713: {e.stderr}\\\", file=sys.stderr)\\n return None\\n except json.JSONDecodeError as e:\\n print(f\\\"Error parsing JSON from command: {cmd}\\\", file=sys.stderr)\\n print(f\\\"Error: {e}\\\", file=sys.stderr)\\n return None\\n\\ndef main():\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n \\n # Get current time and 14 days ago\\n end_date = datetime.utcnow()\\n start_date = end_date - timedelta(days=14)\\n \\n print(f\\\"Collecting workflow statistics from {start_date.isoformat()} to {end_date.isoformat()}\\\", file=sys.stderr)\\n \\n # List all workflows\\n workflows_data = run_gh_command(f\\\"gh workflow list --repo {owner}/{repo} --json id,name,path --limit 200\\\")\\n if not workflows_data:\\n print(\\\"Failed to fetch workflows\\\", file=sys.stderr)\\n sys.exit(1)\\n \\n # Filter only .lock.yml workflows\\n lock_workflows = [w for w in workflows_data if w['path'].endswith('.lock.yml')]\\n print(f\\\"Found {len(lock_workflows)} agentic workflows (.lock.yml files)\\\", file=sys.stderr)\\n \\n results = []\\n \\n for i, workflow in enumerate(lock_workflows, 1):\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"[{i}/{len(lock_workflows)}] Processing: {workflow_name}\\\", file=sys.stderr)\\n \\n # Get workflow runs for the past 14 days\\n runs_data = run_gh_command(\\n f\\\"gh run list --repo {owner}/{repo} --workflow {workflow_id} \\\"\\n f\\\"--limit 100 --json conclusion,durationMs,status,createdAt\\\"\\n )\\n \\n if not runs_data:\\n print(f\\\" Warning: Failed to fetch runs for workflow {workflow_id}\\\", file=sys.stderr)\\n continue\\n \\n # Filter runs from the past 14 days\\n filtered_runs = []\\n for run in runs_data:\\n try:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if created_at \\u003e= start_date:\\n filtered_runs.append(run)\\n except (KeyError, ValueError) as e:\\n continue\\n \\n # Calculate statistics\\n total_runs = len(filtered_runs)\\n successful_runs = sum(1 for r in filtered_runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in filtered_runs if r.get('conclusion') == 'failure')\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0\\n \\n # Calculate average duration (in seconds)\\n durations = [r.get('durationMs', 0) for r in filtered_runs if r.get('durationMs')]\\n avg_duration = (sum(durations) / len(durations) / 1000) if durations else 0\\n \\n results.append({\\n \\\"workflow_name\\\": workflow_name,\\n \\\"workflow_path\\\": workflow_path,\\n \\\"workflow_id\\\": workflow_id,\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2)\\n })\\n \\n print(f\\\" Runs: {total_runs}, Success: {successful_runs}, Failed: {failed_runs}, \\\"\\n f\\\"Success Rate: {success_rate:.2f}%\\\", file=sys.stderr)\\n \\n # Sort by total runs (descending)\\n results.sort(key=lambda x: x['total_runs'], reverse=True)\\n \\n # Create final output\\n output = {\\n \\\"metadata\\\": {\\n \\\"owner\\\": owner,\\n \\\"repo\\\": repo,\\n \\\"data_collection_date\\\": end_date.isoformat() + \\\"Z\\\",\\n \\\"period_days\\\": 14,\\n \\\"start_date\\\": start_date.isoformat() + \\\"Z\\\",\\n \\\"end_date\\\":

Line 10647: {e.stderr}\\\", file=sys.stderr)\\n return None\\n except json.JSONDecodeError as e:\\n print(f\\\"Error parsing JSON from command: {cmd}\\\", file=sys.stderr)\\n print(f\\\"Output: {result.stdout}\\\", file=sys.stderr)\\n return None\\n\\n# Get all workflows\\nprint(\\\"Fetching workflows...\\\", file=sys.stderr)\\nworkflows_cmd = f'gh workflow list --repo {OWNER}/{REPO} --json id,name,path'\\nworkflows_result = run_gh_command(workflows_cmd)\\n\\nif not workflows_result:\\n print(\\\"Failed to fetch workflows\\\", file=sys.stderr)\\n sys.exit(1)\\n\\n# Filter for agentic workflows (ending in .lock.yml)\\nagentic_workflows = [w for w in workflows_result if w['path'].endswith('.lock.yml')]\\n\\nprint(f\\\"Found {len(workflows_result)} total workflows, {len(agentic_workflows)} agentic workflows\\\", file=sys.stderr)\\n\\n# Calculate date range\\nend_date = datetime.utcnow()\\nstart_date = end_date - timedelta(days=DAYS)\\nstart_date_iso = start_date.isoformat() + \\\"Z\\\"\\n\\nprint(f\\\"Collecting runs from {start_date_iso} to {end_date.isoformat()}Z\\\", file=sys.stderr)\\n\\nresults = []\\n\\nfor workflow in agentic_workflows:\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"Processing {workflow_name}...\\\", file=sys.stderr)\\n \\n # Get all runs for this workflow from the past 14 days\\n runs_cmd = f'gh run list --repo {OWNER}/{REPO} --workflow {workflow_id} --limit 100 --json conclusion,duration,status,createdAt,databaseId'\\n runs_result = run_gh_command(runs_cmd)\\n \\n if not runs_result:\\n print(f\\\" Warning: Could not fetch runs for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Filter runs from the past 14 days\\n relevant_runs = []\\n for run in runs_result:\\n try:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if created_at >= start_date.replace(tzinfo=created_at.tzinfo):\\n relevant_runs.append(run)\\n except (KeyError, ValueError) as e:\\n print(f\\\" Warning: Could not parse run timestamp: {e}\\\", file=sys.stderr)\\n continue\\n \\n if not relevant_runs:\\n print(f\\\" No runs found in the past {DAYS} days for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Calculate statistics\\n total_runs = len(relevant_runs)\\n successful_runs = sum(1 for r in relevant_runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in relevant_runs if r.get('conclusion') == 'failure')\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs > 0 else 0\\n \\n # Calculate average duration (in seconds)\\n durations = []\\n for run in relevant_runs:\\n duration = run.get('duration')\\n if duration is not None:\\n durations.append(duration)\\n \\n avg_duration = sum(durations) / len(durations) if durations else 0\\n \\n workflow_data = {\\n \\\"workflow_name\\\": workflow_name,\\n \\\"workflow_path\\\": workflow_path,\\n \\\"workflow_id\\\": workflow_id,\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2),\\n \\\"data_collection_period_days\\\": DAYS,\\n \\\"start_date\\\": start_date_iso,\\n \\\"end_date\\\": end_date.isoformat() + \\\"Z\\\"\\n }\\n \\n results.append(workflow_data)\\n \\n print(f\\\" Total: {total_runs}, Success: {successful_runs}, Failed: {failed_runs}, Success Rate: {success_rate:.2f}%\\\", file=sys.stderr)\\n\\n# Create output directory\\noutput_dir = \\\"/tmp/gh-aw/agent\\\"\\nos.makedirs(output_dir, exist_ok=True)\\n\\n# Write results to JSON file\\noutput_file = os.path.join(output

Line 10020: {e.stderr}\\\")\\n exit(1)\\n\\nEOF\\n\",\"description\":\"Collect PR data from gh-aw repo\"}", (Pattern: Generic ERROR messages, Raw log: "arguments": "{\"command\":\"cd /home/runner/work/gh-aw/gh-aw && python3 << 'EOF'\\nimport json\\nimport subprocess\\nim...)

Line 111: MCP error -32000: Connection closed (Pattern: Generic ERROR messages, Raw log: 2026-01-03T04:57:00.209Z [ERROR] Failed to start MCP client for agentic_workflows: McpError: MCP error -32000: Connectio...)

Error: EACCES: permission denied, open '/tmp/gh-aw/sandbox/firewall/logs/access.log'

An error has occurred while creating the zip file for upload

The action 'Execute GitHub Copilot CLI' has timed out after 30 minutes.

Error reading agent output file: ENOENT: no such file or directory, open '/tmp/gh-aw/safeoutputs/agent_output.json'

Error reading agent output file: ENOENT: no such file or directory, open '/tmp/gh-aw/safeoutputs/agent_output.json'

Unable to download artifact(s): Artifact not found for name: agent-output Please ensure that your artifact is not expired and the artifact was uploaded using a compatible version of toolkit/upload-artifact. For more information, visit the GitHub Artifacts FAQ: https://github.com/actions/toolkit/blob/main/packages/artifact/docs/faq.md

Line 41740: Failed to fetch runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef calculate_workflow_stats(workflow: Dict[str, Any], runs: List[Dict[str, Any]], period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for a workflow.\\\"\\\"\\\"\\n total_runs = len(runs)\\n successful_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"success\\\")\\n failed_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"failure\\\")\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (only for completed runs with duration data)\\n durations = []\\n for run in runs:\\n if run.get(\\\"conclusion\\\") in [\\\"success\\\", \\\"failure\\\"] and run.get(\\\"run_started_at\\\"):\\n started = datetime.fromisoformat(run[\\\"run_started_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n updated = datetime.fromisoformat(run[\\\"updated_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n duration = (updated - started).total_seconds()\\n if duration \\u003e 0:\\n durations.append(duration)\\n \\n avg_duration = sum(durations) / len(durations) if durations else 0.0\\n \\n return {\\n \\\"workflow_name\\\": workflow.get(\\\"name\\\", \\\"\\\"),\\n \\\"workflow_path\\\": workflow.get(\\\"path\\\", \\\"\\\"),\\n \\\"workflow_id\\\": workflow.get(\\\"id\\\", 0),\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate_percent\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2),\\n \\\"data_collection_date\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n }\\n\\n\\ndef collect_statistics(owner: str, repo: str, period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Collect workflow statistics for the repository.\\\"\\\"\\\"\\n since_date = (datetime.now(timezone.utc) - timedelta(days=period_days)).isoformat()\\n \\n # Get all workflows\\n all_workflows = get_workflows(owner, repo)\\n \\n # Filter for agentic workflows\\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n \\n # Collect stats for each workflow\\n workflow_stats = []\\n for workflow in agentic_workflows:\\n print(f\\\"Processing: {workflow.get('name')} ({workflow.get('path')})\\\", file=sys.stderr)\\n runs = get_workflow_runs(owner, repo, workflow[\\\"id\\\"], since_date)\\n stats = calculate_workflow_stats(workflow, runs, period_days)\\n workflow_stats.append(stats)\\n \\n # Calculate summary\\n total_runs = sum(w[\\\"total_runs\\\"] for w in workflow_stats)\\n total_successful = sum(w[\\\"successful_runs\\\"] for w in workflow_stats)\\n total_failed = sum(w[\\\"failed_runs\\\"] for w in workflow_stats)\\n overall_success_rate = (total_successful / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n return {\\n \\\"summary\\\": {\\n \\\"total_workflows\\\": len(workflow_stats),\\n \\\"total_runs\\\": total_runs,\\n \\\"total_successful\\\": total_successful,\\n \\\"total_failed\\\": total_failed,\\n \\\"overall_success_rate_percent\\\": round(overall_success_rate, 2),\\n \\\"collection_timestamp\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n },\\n \\\"workflows\\\": workflow_stats\\n }\\n\\n\\ndef main():\\n \\\"\\\"\\\"Main entry point.\\\"\\\"\\\"\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n output_file = \\\"/home/runner/work/gh-aw/gh-aw/workflow_runs.json\\\"\\n \\n print(f\\\"Collecting workflow statistics for {owner}/{repo}\\\", file=sys.stderr)\\n print(f\\\"Period: past {period_da

Line 41518: Failed to fetch runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef calculate_workflow_stats(workflow: Dict[str, Any], runs: List[Dict[str, Any]], period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for a workflow.\\\"\\\"\\\"\\n total_runs = len(runs)\\n successful_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"success\\\")\\n failed_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"failure\\\")\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (only for completed runs with duration data)\\n durations = []\\n for run in runs:\\n if run.get(\\\"conclusion\\\") in [\\\"success\\\", \\\"failure\\\"] and run.get(\\\"run_started_at\\\"):\\n started = datetime.fromisoformat(run[\\\"run_started_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n updated = datetime.fromisoformat(run[\\\"updated_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n duration = (updated - started).total_seconds()\\n if duration \\u003e 0:\\n durations.append(duration)\\n \\n avg_duration = sum(durations) / len(durations) if durations else 0.0\\n \\n return {\\n \\\"workflow_name\\\": workflow.get(\\\"name\\\", \\\"\\\"),\\n \\\"workflow_path\\\": workflow.get(\\\"path\\\", \\\"\\\"),\\n \\\"workflow_id\\\": workflow.get(\\\"id\\\", 0),\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate_percent\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2),\\n \\\"data_collection_date\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n }\\n\\n\\ndef collect_statistics(owner: str, repo: str, period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Collect workflow statistics for the repository.\\\"\\\"\\\"\\n since_date = (datetime.now(timezone.utc) - timedelta(days=period_days)).isoformat()\\n \\n # Get all workflows\\n all_workflows = get_workflows(owner, repo)\\n \\n # Filter for agentic workflows\\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n \\n # Collect stats for each workflow\\n workflow_stats = []\\n for workflow in agentic_workflows:\\n print(f\\\"Processing: {workflow.get('name')} ({workflow.get('path')})\\\", file=sys.stderr)\\n runs = get_workflow_runs(owner, repo, workflow[\\\"id\\\"], since_date)\\n stats = calculate_workflow_stats(workflow, runs, period_days)\\n workflow_stats.append(stats)\\n \\n # Calculate summary\\n total_runs = sum(w[\\\"total_runs\\\"] for w in workflow_stats)\\n total_successful = sum(w[\\\"successful_runs\\\"] for w in workflow_stats)\\n total_failed = sum(w[\\\"failed_runs\\\"] for w in workflow_stats)\\n overall_success_rate = (total_successful / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n return {\\n \\\"summary\\\": {\\n \\\"total_workflows\\\": len(workflow_stats),\\n \\\"total_runs\\\": total_runs,\\n \\\"total_successful\\\": total_successful,\\n \\\"total_failed\\\": total_failed,\\n \\\"overall_success_rate_percent\\\": round(overall_success_rate, 2),\\n \\\"collection_timestamp\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n },\\n \\\"workflows\\\": workflow_stats\\n }\\n\\n\\ndef main():\\n \\\"\\\"\\\"Main entry point.\\\"\\\"\\\"\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n output_file = \\\"/home/runner/work/gh-aw/gh-aw/workflow_runs.json\\\"\\n \\n print(f\\\"Collecting workflow statistics for {owner}/{repo}\\\", file=sys.stderr)\\n print(f\\\"Period: past {period_da

Line 41415: Failed to fetch runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef calculate_workflow_stats(workflow: Dict[str, Any], runs: List[Dict[str, Any]], period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for a workflow.\\\"\\\"\\\"\\n total_runs = len(runs)\\n successful_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"success\\\")\\n failed_runs = sum(1 for r in runs if r.get(\\\"conclusion\\\") == \\\"failure\\\")\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (only for completed runs with duration data)\\n durations = []\\n for run in runs:\\n if run.get(\\\"conclusion\\\") in [\\\"success\\\", \\\"failure\\\"] and run.get(\\\"run_started_at\\\"):\\n started = datetime.fromisoformat(run[\\\"run_started_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n updated = datetime.fromisoformat(run[\\\"updated_at\\\"].replace(\\\"Z\\\", \\\"+00:00\\\"))\\n duration = (updated - started).total_seconds()\\n if duration \\u003e 0:\\n durations.append(duration)\\n \\n avg_duration = sum(durations) / len(durations) if durations else 0.0\\n \\n return {\\n \\\"workflow_name\\\": workflow.get(\\\"name\\\", \\\"\\\"),\\n \\\"workflow_path\\\": workflow.get(\\\"path\\\", \\\"\\\"),\\n \\\"workflow_id\\\": workflow.get(\\\"id\\\", 0),\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate_percent\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2),\\n \\\"data_collection_date\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n }\\n\\n\\ndef collect_statistics(owner: str, repo: str, period_days: int) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Collect workflow statistics for the repository.\\\"\\\"\\\"\\n since_date = (datetime.now(timezone.utc) - timedelta(days=period_days)).isoformat()\\n \\n # Get all workflows\\n all_workflows = get_workflows(owner, repo)\\n \\n # Filter for agentic workflows\\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n \\n # Collect stats for each workflow\\n workflow_stats = []\\n for workflow in agentic_workflows:\\n print(f\\\"Processing: {workflow.get('name')} ({workflow.get('path')})\\\", file=sys.stderr)\\n runs = get_workflow_runs(owner, repo, workflow[\\\"id\\\"], since_date)\\n stats = calculate_workflow_stats(workflow, runs, period_days)\\n workflow_stats.append(stats)\\n \\n # Calculate summary\\n total_runs = sum(w[\\\"total_runs\\\"] for w in workflow_stats)\\n total_successful = sum(w[\\\"successful_runs\\\"] for w in workflow_stats)\\n total_failed = sum(w[\\\"failed_runs\\\"] for w in workflow_stats)\\n overall_success_rate = (total_successful / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n return {\\n \\\"summary\\\": {\\n \\\"total_workflows\\\": len(workflow_stats),\\n \\\"total_runs\\\": total_runs,\\n \\\"total_successful\\\": total_successful,\\n \\\"total_failed\\\": total_failed,\\n \\\"overall_success_rate_percent\\\": round(overall_success_rate, 2),\\n \\\"collection_timestamp\\\": datetime.now(timezone.utc).isoformat(),\\n \\\"period_days\\\": period_days\\n },\\n \\\"workflows\\\": workflow_stats\\n }\\n\\n\\ndef main():\\n \\\"\\\"\\\"Main entry point.\\\"\\\"\\\"\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n output_file = \\\"/home/runner/work/gh-aw/gh-aw/workflow_runs.json\\\"\\n \\n print(f\\\"Collecting workflow statistics for {owner}/{repo}\\\", file=sys.stderr)\\n print(f\\\"Period: past {period_da

Line 37616: Error fetching runs for workflow {workflow_id}: {e}\", file=sys.stderr)\n return []\n except json.JSONDecodeError as e:\n print(f\"Warning: Error parsing JSON for workflow {workflow_id}: {e}\", file=sys.stderr)\n return []\n\n\ndef filter_runs_by_date(runs: List[Dict[str, Any]], start_date: datetime, end_date: datetime) -> List[Dict[str, Any]]:\n \"\"\"Filter runs within the specified date range.\"\"\"\n filtered = []\n for run in runs:\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\n if start_date <= created_at <= end_date:\n filtered.append(run)\n return filtered\n\n\ndef calculate_statistics(runs: List[Dict[str, Any]]) -> Dict[str, Any]:\n \"\"\"Calculate statistics for workflow runs.\"\"\"\n total_runs = len(runs)\n \n if total_runs == 0:\n return {\n \"total_runs\": 0,\n \"successful_runs\": 0,\n \"failed_runs\": 0,\n \"success_rate\": 0.0,\n \"average_duration_seconds\": 0.0\n }\n \n successful_runs = sum(1 for r in runs if r.get('conclusion') == 'success')\n failed_runs = sum(1 for r in runs if r.get('conclusion') == 'failure')\n success_rate = (successful_runs / total_runs * 100) if total_runs > 0 else 0.0\n \n # Calculate average duration (durationMs is in milliseconds)\n durations = [r.get('durationMs', 0) for r in runs if r.get('durationMs') is not None]\n avg_duration_ms = sum(durations) / len(durations) if durations else 0\n avg_duration_seconds = avg_duration_ms / 1000\n \n return {\n \"total_runs\": total_runs,\n \"successful_runs\": successful_runs,\n \"failed_runs\": failed_runs,\n \"success_rate\": round(success_rate, 2),\n \"average_duration_seconds\": round(avg_duration_seconds, 2)\n }\n\n\ndef get_date_range(runs: List[Dict[str, Any]]) -> Dict[str, str]:\n \"\"\"Get the actual date range of runs.\"\"\"\n if not runs:\n return {\"start\": None, \"end\": None}\n \n dates = [datetime.fromisoformat(r['createdAt'].replace('Z', '+00:00')) for r in runs]\n return {\n \"start\": min(dates).isoformat(),\n \"end\": max(dates).isoformat()\n }\n\n\ndef main():\n owner = \"githubnext\"\n repo = \"gh-aw\"\n period_days = 14\n \n # Calculate date range\n end_date = datetime.now(timezone.utc)\n start_date = end_date - timedelta(days=period_days)\n \n print(f\"Fetching workflows from {owner}/{repo}...\", file=sys.stderr)\n all_workflows = get_all_workflows(owner, repo)\n print(f\"Total workflows found: {len(all_workflows)}\", file=sys.stderr)\n \n agentic_workflows = filter_agentic_workflows(all_workflows)\n print(f\"Agentic workflows (.lock.yml): {len(agentic_workflows)}\", file=sys.stderr)\n \n workflow_stats = []\n total_runs_analyzed = 0\n \n for idx, workflow in enumerate(agentic_workflows, 1):\n workflow_id = workflow['id']\n workflow_name = workflow['name']\n workflow_path = workflow['path']\n \n print(f\"Processing {idx}/{len(agentic_workflows)}: {workflow_name} (ID: {workflow_id})...\", file=sys.stderr)\n \n # Get runs for this workflow\n runs = get_workflow_runs(owner, repo, workflow_id, limit=50)\n \n # Filter runs by date\n filtered_runs = filter_runs_by_date(runs, start_date, end_date)\n \n if not filtered_runs:\n print(f\" No runs in the past {period_days} days\", file=sys.stderr)\n continue\n \n # Calculate statistics\n stats = calculate_statistics(filtered_runs)\n date_range = get_date_range(filtered_runs)\n \n total_runs_analyzed += stats['total_runs']\n \n workflow_stats.append({\n \"workflow_id\": workflow_id,\n \"workflow_name\": workflow_name,\n \"workflow_path\": workflow_path,\n \"total_runs\": stats['total_runs'],\n \"successf

Line 37485: Error fetching runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n except json.JSONDecodeError as e:\\n print(f\\\"Warning: Error parsing JSON for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef filter_runs_by_date(runs: List[Dict[str, Any]], start_date: datetime, end_date: datetime) -\\u003e List[Dict[str, Any]]:\\n \\\"\\\"\\\"Filter runs within the specified date range.\\\"\\\"\\\"\\n filtered = []\\n for run in runs:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if start_date \\u003c= created_at \\u003c= end_date:\\n filtered.append(run)\\n return filtered\\n\\n\\ndef calculate_statistics(runs: List[Dict[str, Any]]) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for workflow runs.\\\"\\\"\\\"\\n total_runs = len(runs)\\n \\n if total_runs == 0:\\n return {\\n \\\"total_runs\\\": 0,\\n \\\"successful_runs\\\": 0,\\n \\\"failed_runs\\\": 0,\\n \\\"success_rate\\\": 0.0,\\n \\\"average_duration_seconds\\\": 0.0\\n }\\n \\n successful_runs = sum(1 for r in runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in runs if r.get('conclusion') == 'failure')\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (durationMs is in milliseconds)\\n durations = [r.get('durationMs', 0) for r in runs if r.get('durationMs') is not None]\\n avg_duration_ms = sum(durations) / len(durations) if durations else 0\\n avg_duration_seconds = avg_duration_ms / 1000\\n \\n return {\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration_seconds, 2)\\n }\\n\\n\\ndef get_date_range(runs: List[Dict[str, Any]]) -\\u003e Dict[str, str]:\\n \\\"\\\"\\\"Get the actual date range of runs.\\\"\\\"\\\"\\n if not runs:\\n return {\\\"start\\\": None, \\\"end\\\": None}\\n \\n dates = [datetime.fromisoformat(r['createdAt'].replace('Z', '+00:00')) for r in runs]\\n return {\\n \\\"start\\\": min(dates).isoformat(),\\n \\\"end\\\": max(dates).isoformat()\\n }\\n\\n\\ndef main():\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n \\n # Calculate date range\\n end_date = datetime.now(timezone.utc)\\n start_date = end_date - timedelta(days=period_days)\\n \\n print(f\\\"Fetching workflows from {owner}/{repo}...\\\", file=sys.stderr)\\n all_workflows = get_all_workflows(owner, repo)\\n print(f\\\"Total workflows found: {len(all_workflows)}\\\", file=sys.stderr)\\n \\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n print(f\\\"Agentic workflows (.lock.yml): {len(agentic_workflows)}\\\", file=sys.stderr)\\n \\n workflow_stats = []\\n total_runs_analyzed = 0\\n \\n for idx, workflow in enumerate(agentic_workflows, 1):\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"Processing {idx}/{len(agentic_workflows)}: {workflow_name} (ID: {workflow_id})...\\\", file=sys.stderr)\\n \\n # Get runs for this workflow\\n runs = get_workflow_runs(owner, repo, workflow_id, limit=50)\\n \\n # Filter runs by date\\n filtered_runs = filter_runs_by_date(runs, start_date, end_date)\\n \\n if not filtered_runs:\\n print(f\\\" No runs in the past {period_days} days\\\", file=sys.stderr)\\n continue\\n \\n # Calculate statistics\\n stats = calculate_statistics(filtered_runs)\\n date_range = get_date_range(filtered_runs)\\n \\n total_runs_analyzed += stats['tota

Line 35112: Error fetching runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n except json.JSONDecodeError as e:\\n print(f\\\"Warning: Error parsing JSON for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef filter_runs_by_date(runs: List[Dict[str, Any]], start_date: datetime, end_date: datetime) -\\u003e List[Dict[str, Any]]:\\n \\\"\\\"\\\"Filter runs within the specified date range.\\\"\\\"\\\"\\n filtered = []\\n for run in runs:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if start_date \\u003c= created_at \\u003c= end_date:\\n filtered.append(run)\\n return filtered\\n\\n\\ndef calculate_statistics(runs: List[Dict[str, Any]]) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for workflow runs.\\\"\\\"\\\"\\n total_runs = len(runs)\\n \\n if total_runs == 0:\\n return {\\n \\\"total_runs\\\": 0,\\n \\\"successful_runs\\\": 0,\\n \\\"failed_runs\\\": 0,\\n \\\"success_rate\\\": 0.0,\\n \\\"average_duration_seconds\\\": 0.0\\n }\\n \\n successful_runs = sum(1 for r in runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in runs if r.get('conclusion') == 'failure')\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (durationMs is in milliseconds)\\n durations = [r.get('durationMs', 0) for r in runs if r.get('durationMs') is not None]\\n avg_duration_ms = sum(durations) / len(durations) if durations else 0\\n avg_duration_seconds = avg_duration_ms / 1000\\n \\n return {\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration_seconds, 2)\\n }\\n\\n\\ndef get_date_range(runs: List[Dict[str, Any]]) -\\u003e Dict[str, str]:\\n \\\"\\\"\\\"Get the actual date range of runs.\\\"\\\"\\\"\\n if not runs:\\n return {\\\"start\\\": None, \\\"end\\\": None}\\n \\n dates = [datetime.fromisoformat(r['createdAt'].replace('Z', '+00:00')) for r in runs]\\n return {\\n \\\"start\\\": min(dates).isoformat(),\\n \\\"end\\\": max(dates).isoformat()\\n }\\n\\n\\ndef main():\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n \\n # Calculate date range\\n end_date = datetime.now(timezone.utc)\\n start_date = end_date - timedelta(days=period_days)\\n \\n print(f\\\"Fetching workflows from {owner}/{repo}...\\\", file=sys.stderr)\\n all_workflows = get_all_workflows(owner, repo)\\n print(f\\\"Total workflows found: {len(all_workflows)}\\\", file=sys.stderr)\\n \\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n print(f\\\"Agentic workflows (.lock.yml): {len(agentic_workflows)}\\\", file=sys.stderr)\\n \\n workflow_stats = []\\n total_runs_analyzed = 0\\n \\n for idx, workflow in enumerate(agentic_workflows, 1):\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"Processing {idx}/{len(agentic_workflows)}: {workflow_name} (ID: {workflow_id})...\\\", file=sys.stderr)\\n \\n # Get runs for this workflow\\n runs = get_workflow_runs(owner, repo, workflow_id, limit=50)\\n \\n # Filter runs by date\\n filtered_runs = filter_runs_by_date(runs, start_date, end_date)\\n \\n if not filtered_runs:\\n print(f\\\" No runs in the past {period_days} days\\\", file=sys.stderr)\\n continue\\n \\n # Calculate statistics\\n stats = calculate_statistics(filtered_runs)\\n date_range = get_date_range(filtered_runs)\\n \\n total_runs_analyzed += stats['tota

Line 34803: Error fetching runs for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n except json.JSONDecodeError as e:\\n print(f\\\"Warning: Error parsing JSON for workflow {workflow_id}: {e}\\\", file=sys.stderr)\\n return []\\n\\n\\ndef filter_runs_by_date(runs: List[Dict[str, Any]], start_date: datetime, end_date: datetime) -\\u003e List[Dict[str, Any]]:\\n \\\"\\\"\\\"Filter runs within the specified date range.\\\"\\\"\\\"\\n filtered = []\\n for run in runs:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if start_date \\u003c= created_at \\u003c= end_date:\\n filtered.append(run)\\n return filtered\\n\\n\\ndef calculate_statistics(runs: List[Dict[str, Any]]) -\\u003e Dict[str, Any]:\\n \\\"\\\"\\\"Calculate statistics for workflow runs.\\\"\\\"\\\"\\n total_runs = len(runs)\\n \\n if total_runs == 0:\\n return {\\n \\\"total_runs\\\": 0,\\n \\\"successful_runs\\\": 0,\\n \\\"failed_runs\\\": 0,\\n \\\"success_rate\\\": 0.0,\\n \\\"average_duration_seconds\\\": 0.0\\n }\\n \\n successful_runs = sum(1 for r in runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in runs if r.get('conclusion') == 'failure')\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0.0\\n \\n # Calculate average duration (durationMs is in milliseconds)\\n durations = [r.get('durationMs', 0) for r in runs if r.get('durationMs') is not None]\\n avg_duration_ms = sum(durations) / len(durations) if durations else 0\\n avg_duration_seconds = avg_duration_ms / 1000\\n \\n return {\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration_seconds, 2)\\n }\\n\\n\\ndef get_date_range(runs: List[Dict[str, Any]]) -\\u003e Dict[str, str]:\\n \\\"\\\"\\\"Get the actual date range of runs.\\\"\\\"\\\"\\n if not runs:\\n return {\\\"start\\\": None, \\\"end\\\": None}\\n \\n dates = [datetime.fromisoformat(r['createdAt'].replace('Z', '+00:00')) for r in runs]\\n return {\\n \\\"start\\\": min(dates).isoformat(),\\n \\\"end\\\": max(dates).isoformat()\\n }\\n\\n\\ndef main():\\n owner = \\\"githubnext\\\"\\n repo = \\\"gh-aw\\\"\\n period_days = 14\\n \\n # Calculate date range\\n end_date = datetime.now(timezone.utc)\\n start_date = end_date - timedelta(days=period_days)\\n \\n print(f\\\"Fetching workflows from {owner}/{repo}...\\\", file=sys.stderr)\\n all_workflows = get_all_workflows(owner, repo)\\n print(f\\\"Total workflows found: {len(all_workflows)}\\\", file=sys.stderr)\\n \\n agentic_workflows = filter_agentic_workflows(all_workflows)\\n print(f\\\"Agentic workflows (.lock.yml): {len(agentic_workflows)}\\\", file=sys.stderr)\\n \\n workflow_stats = []\\n total_runs_analyzed = 0\\n \\n for idx, workflow in enumerate(agentic_workflows, 1):\\n workflow_id = workflow['id']\\n workflow_name = workflow['name']\\n workflow_path = workflow['path']\\n \\n print(f\\\"Processing {idx}/{len(agentic_workflows)}: {workflow_name} (ID: {workflow_id})...\\\", file=sys.stderr)\\n \\n # Get runs for this workflow\\n runs = get_workflow_runs(owner, repo, workflow_id, limit=50)\\n \\n # Filter runs by date\\n filtered_runs = filter_runs_by_date(runs, start_date, end_date)\\n \\n if not filtered_runs:\\n print(f\\\" No runs in the past {period_days} days\\\", file=sys.stderr)\\n continue\\n \\n # Calculate statistics\\n stats = calculate_statistics(filtered_runs)\\n date_range = get_date_range(filtered_runs)\\n \\n total_runs_analyzed += stats['tota

Line 17358: Failed to fetch runs for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Calculate stats\\n stats = calculate_stats(runs, start_date)\\n \\n workflow_stats.append({\\n 'workflow_name': workflow_name,\\n 'workflow_path': workflow_path,\\n 'workflow_id': workflow_id,\\n **stats\\n })\\n \\n print(f\\\" Total: {stats['total_runs']}, Success: {stats['successful_runs']}, \\\"\\n f\\\"Failed: {stats['failed_runs']}, Rate: {stats['success_rate']}%\\\", file=sys.stderr)\\n \\n # Build final output\\n output = {\\n 'metadata': {\\n 'owner': 'githubnext',\\n 'repo': 'gh-aw',\\n 'data_collection_date': end_date.isoformat(),\\n 'period_days': 14,\\n 'start_date': start_date.isoformat(),\\n 'end_date': end_date.isoformat(),\\n 'workflow_count': len(workflow_stats)\\n },\\n 'workflows': sorted(workflow_stats, key=lambda x: x['total_runs'], reverse=True)\\n }\\n \\n # Write to file\\n output_path = '/tmp/gh-aw/agent/workflow_runs.json'\\n with open(output_path, 'w') as f:\\n json.dump(output, f, indent=2)\\n \\n print(f\\\"\\\\n✓ Statistics saved to {output_path}\\\", file=sys.stderr)\\n print(f\\\"✓ Collected data for {len(workflow_stats)} workflows\\\", file=sys.stderr)\\n\\nif __name__ == '__main__':\\n main()\\nSCRIPT_EOF\\ncat /tmp/collect_stats.py\",\"description\":\"Create Python script to collect workflow statistics\"}", (Pattern: Generic WARNING messages, Raw log: "arguments": "{\"command\":\"cat \\u003e /tmp/collect_stats.py \\u003c\\u003c 'SCRIPT_EOF'\\nimport json\\nimport subpro...)

Line 14713: Failed to fetch runs for workflow {workflow_id}\\\", file=sys.stderr)\\n continue\\n \\n # Filter runs from the past 14 days\\n filtered_runs = []\\n for run in runs_data:\\n try:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if created_at \\u003e= start_date:\\n filtered_runs.append(run)\\n except (KeyError, ValueError) as e:\\n continue\\n \\n # Calculate statistics\\n total_runs = len(filtered_runs)\\n successful_runs = sum(1 for r in filtered_runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in filtered_runs if r.get('conclusion') == 'failure')\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs \\u003e 0 else 0\\n \\n # Calculate average duration (in seconds)\\n durations = [r.get('durationMs', 0) for r in filtered_runs if r.get('durationMs')]\\n avg_duration = (sum(durations) / len(durations) / 1000) if durations else 0\\n \\n results.append({\\n \\\"workflow_name\\\": workflow_name,\\n \\\"workflow_path\\\": workflow_path,\\n \\\"workflow_id\\\": workflow_id,\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2)\\n })\\n \\n print(f\\\" Runs: {total_runs}, Success: {successful_runs}, Failed: {failed_runs}, \\\"\\n f\\\"Success Rate: {success_rate:.2f}%\\\", file=sys.stderr)\\n \\n # Sort by total runs (descending)\\n results.sort(key=lambda x: x['total_runs'], reverse=True)\\n \\n # Create final output\\n output = {\\n \\\"metadata\\\": {\\n \\\"owner\\\": owner,\\n \\\"repo\\\": repo,\\n \\\"data_collection_date\\\": end_date.isoformat() + \\\"Z\\\",\\n \\\"period_days\\\": 14,\\n \\\"start_date\\\": start_date.isoformat() + \\\"Z\\\",\\n \\\"end_date\\\": end_date.isoformat() + \\\"Z\\\",\\n \\\"workflow_count\\\": len(results)\\n },\\n \\\"workflows\\\": results\\n }\\n \\n # Save to file\\n output_path = \\\"/tmp/gh-aw/agent/workflow_runs.json\\\"\\n with open(output_path, 'w') as f:\\n json.dump(output, f, indent=2)\\n \\n print(f\\\"\\\\nStatistics saved to: {output_path}\\\", file=sys.stderr)\\n print(f\\\"Total workflows analyzed: {len(results)}\\\", file=sys.stderr)\\n print(f\\\"Total runs across all workflows: {sum(w['total_runs'] for w in results)}\\\", file=sys.stderr)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\nEOF\\npython3 /tmp/collect_stats.py\\n\",\"description\":\"Create and run Python script to collect workflow statistics\",\"initial_wait\":120,\"mode\":\"sync\"}", (Pattern: Generic WARNING messages, Raw log: "arguments": "{\"command\":\"cat \\u003e /tmp/collect_stats.py \\u003c\\u003c 'EOF'\\nimport json\\nimport subprocess\\n...)

Line 10647: Could not fetch runs for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Filter runs from the past 14 days\\n relevant_runs = []\\n for run in runs_result:\\n try:\\n created_at = datetime.fromisoformat(run['createdAt'].replace('Z', '+00:00'))\\n if created_at >= start_date.replace(tzinfo=created_at.tzinfo):\\n relevant_runs.append(run)\\n except (KeyError, ValueError) as e:\\n print(f\\\" Warning: Could not parse run timestamp: {e}\\\", file=sys.stderr)\\n continue\\n \\n if not relevant_runs:\\n print(f\\\" No runs found in the past {DAYS} days for {workflow_name}\\\", file=sys.stderr)\\n continue\\n \\n # Calculate statistics\\n total_runs = len(relevant_runs)\\n successful_runs = sum(1 for r in relevant_runs if r.get('conclusion') == 'success')\\n failed_runs = sum(1 for r in relevant_runs if r.get('conclusion') == 'failure')\\n \\n # Calculate success rate\\n success_rate = (successful_runs / total_runs * 100) if total_runs > 0 else 0\\n \\n # Calculate average duration (in seconds)\\n durations = []\\n for run in relevant_runs:\\n duration = run.get('duration')\\n if duration is not None:\\n durations.append(duration)\\n \\n avg_duration = sum(durations) / len(durations) if durations else 0\\n \\n workflow_data = {\\n \\\"workflow_name\\\": workflow_name,\\n \\\"workflow_path\\\": workflow_path,\\n \\\"workflow_id\\\": workflow_id,\\n \\\"total_runs\\\": total_runs,\\n \\\"successful_runs\\\": successful_runs,\\n \\\"failed_runs\\\": failed_runs,\\n \\\"success_rate\\\": round(success_rate, 2),\\n \\\"average_duration_seconds\\\": round(avg_duration, 2),\\n \\\"data_collection_period_days\\\": DAYS,\\n \\\"start_date\\\": start_date_iso,\\n \\\"end_date\\\": end_date.isoformat() + \\\"Z\\\"\\n }\\n \\n results.append(workflow_data)\\n \\n print(f\\\" Total: {total_runs}, Success: {successful_runs}, Failed: {failed_runs}, Success Rate: {success_rate:.2f}%\\\", file=sys.stderr)\\n\\n# Create output directory\\noutput_dir = \\\"/tmp/gh-aw/agent\\\"\\nos.makedirs(output_dir, exist_ok=True)\\n\\n# Write results to JSON file\\noutput_file = os.path.join(output_dir, \\\"workflow_runs.json\\\")\\nwith open(output_file, 'w') as f:\\n json.dump({\\n \\\"metadata\\\": {\\n \\\"owner\\\": OWNER,\\n \\\"repo\\\": REPO,\\n \\\"data_collection_date\\\": datetime.utcnow().isoformat() + \\\"Z\\\",\\n \\\"period_days\\\": DAYS,\\n \\\"start_date\\\": start_date_iso,\\n \\\"end_date\\\": end_date.isoformat() + \\\"Z\\\",\\n \\\"workflow_count\\\": len(results)\\n },\\n \\\"workflows\\\": results\\n }, f, indent=2)\\n\\nprint(f\\\"\\\\nResults saved to {output_file}\\\", file=sys.stderr)\\nprint(f\\\"Total workflows analyzed: {len(results)}\\\", file=sys.stderr)\\n\\n# Print summary\\nprint(f\\\"\\\\nSummary saved to {output_file}\\\")\\nEOF\\nchmod +x /tmp/collect_workflow_data.py\\npython3 /tmp/collect_workflow_data.py\\n\",\"description\":\"Collect workflow run statistics for the past 14 days\",\"initial_wait\":60}", (Pattern: Generic WARNING messages, Raw log: "arguments": "{\"command\":\"cat > /tmp/collect_workflow_data.py << 'EOF'\\n#!/usr/bin/env python3\\nimport json\\nimpor...)

Failed to process file /tmp/gh-aw/sandbox/firewall/logs/cache.log: EACCES: permission denied, open '/tmp/gh-aw/sandbox/firewall/logs/cache.log'

Failed to process file /tmp/gh-aw/sandbox/firewall/logs/access.log: EACCES: permission denied, open '/tmp/gh-aw/sandbox/firewall/logs/access.log'

Optional runtime import file not found: .github/shared-instructions.md

GitHub MCP lockdown mode enabled for public repository. This prevents the GitHub token from accessing private repositories.

Successfully copied 29 safe-outputs files to /tmp/gh-aw/safeoutputs

Copying safe-outputs files to /tmp/gh-aw/safeoutputs

Successfully copied 16 safe-inputs files to /tmp/gh-aw/safe-inputs

Copying safe-inputs files to /tmp/gh-aw/safe-inputs

Successfully copied 5 prompt files to /tmp/gh-aw/prompts

Copying prompt markdown files to /tmp/gh-aw/prompts

Successfully copied 273 files to /tmp/gh-aw/actions

Found 263 files in /home/runner/work/gh-aw/gh-aw/actions/setup/js

Created directory: /tmp/gh-aw/actions

Copying activation files to /tmp/gh-aw/actions

Successfully copied 29 safe-outputs files to /tmp/gh-aw/safeoutputs

Copying safe-outputs files to /tmp/gh-aw/safeoutputs

Successfully copied 16 safe-inputs files to /tmp/gh-aw/safe-inputs

Copying safe-inputs files to /tmp/gh-aw/safe-inputs

Successfully copied 5 prompt files to /tmp/gh-aw/prompts

Copying prompt markdown files to /tmp/gh-aw/prompts

Successfully copied 273 files to /tmp/gh-aw/actions

Found 263 files in /home/runner/work/gh-aw/gh-aw/actions/setup/js

Created directory: /tmp/gh-aw/actions

Copying activation files to /tmp/gh-aw/actions

Successfully copied 29 safe-outputs files to /tmp/gh-aw/safeoutputs

Copying safe-outputs files to /tmp/gh-aw/safeoutputs

Successfully copied 16 safe-inputs files to /tmp/gh-aw/safe-inputs

Copying safe-inputs files to /tmp/gh-aw/safe-inputs

Successfully copied 5 prompt files to /tmp/gh-aw/prompts

Copying prompt markdown files to /tmp/gh-aw/prompts

Successfully copied 273 files to /tmp/gh-aw/actions

Found 263 files in /home/runner/work/gh-aw/gh-aw/actions/setup/js

Created directory: /tmp/gh-aw/actions

Copying activation files to /tmp/gh-aw/actions

Successfully copied 29 safe-outputs files to /tmp/gh-aw/safeoutputs

Copying safe-outputs files to /tmp/gh-aw/safeoutputs

Successfully copied 16 safe-inputs files to /tmp/gh-aw/safe-inputs

Copying safe-inputs files to /tmp/gh-aw/safe-inputs

Successfully copied 5 prompt files to /tmp/gh-aw/prompts

Copying prompt markdown files to /tmp/gh-aw/prompts

Successfully copied 273 files to /tmp/gh-aw/actions

Found 263 files in /home/runner/work/gh-aw/gh-aw/actions/setup/js

Created directory: /tmp/gh-aw/actions