# Send Task Panner Validator for Agents to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "task-panner-validator", "name": "Task Panner Validator for Agents", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/cerbug45/task-panner-validator", "canonicalUrl": "https://clawhub.ai/cerbug45/task-panner-validator", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/task-panner-validator", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=task-panner-validator", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "API.md", "CHANGELOG.md", "CONTRIBUTING.md", "GITHUB_SETUP.md", "QUICKSTART.md", "README.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "task-panner-validator", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-04T01:20:30.731Z", "expiresAt": "2026-05-11T01:20:30.731Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=task-panner-validator", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=task-panner-validator", "contentDisposition": "attachment; filename=\"task-panner-validator-0.1.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "task-panner-validator" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/task-panner-validator" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/task-panner-validator", "downloadUrl": "https://openagent3.xyz/downloads/task-panner-validator", "agentUrl": "https://openagent3.xyz/skills/task-panner-validator/agent", "manifestUrl": "https://openagent3.xyz/skills/task-panner-validator/agent.json", "briefUrl": "https://openagent3.xyz/skills/task-panner-validator/agent.md" } } ``` ## Documentation ### Task Planner and Validator - Skill Guide This skill provides a secure, step-by-step task management system for AI Agents. ### Quick Installation # Clone the repository git clone https://github.com/cerbug45/task-planner-validator.git cd task-planner-validator # That's it! No dependencies needed - pure Python standard library ### Verify Installation # Run tests python test_basic.py # Run examples python examples.py ### 1. Import and Initialize from task_planner import TaskPlanner # Create planner planner = TaskPlanner(auto_approve=False) ### 2. Define Your Executor def my_executor(action: str, parameters: dict): """Your custom execution logic""" if action == "fetch_data": # Fetch data from API, database, etc. return {"data": [1, 2, 3]} elif action == "process_data": # Process the data return {"processed": True} else: return {"status": "completed"} ### 3. Create a Plan steps = [ { "description": "Fetch user data", "action": "fetch_data", "parameters": {"source": "database"}, "expected_output": "List of users" }, { "description": "Process users", "action": "process_data", "parameters": {"validation": True}, "expected_output": "Processed data" } ] plan = planner.create_plan( title="Data Processing Pipeline", description="Fetch and process user data", steps=steps ) ### 4. Validate and Execute # Validate is_valid, warnings = planner.validate_plan(plan) if warnings: print("Warnings:", warnings) # Approve planner.approve_plan(plan, approved_by="admin") # Execute success, results = planner.execute_plan(plan, my_executor) # Get summary summary = planner.get_execution_summary(plan) print(f"Progress: {summary['progress_percentage']}%") ### Safety Validation Automatically detects dangerous operations: steps = [ { "description": "Delete old files", "action": "delete_files", # ⚠️ Dangerous! "parameters": {"path": "/data/old"}, "safety_check": True, # System will warn "rollback_possible": False # Cannot undo } ] ### Dry Run Mode Test without executing: success, results = planner.execute_plan( plan, my_executor, dry_run=True # Simulate only ) ### Save and Load Plans Persist plans for reuse: # Save planner.save_plan(plan, "my_plan.json") # Load later loaded_plan = planner.load_plan("my_plan.json") # Verify integrity if loaded_plan.verify_integrity(): planner.execute_plan(loaded_plan, my_executor) ### Error Handling Control error behavior: success, results = planner.execute_plan( plan, my_executor, stop_on_error=False # Continue on failures ) # Check results for result in results: if not result['success']: print(f"Step {result['order']} failed: {result['error']}") ### Step Configuration Each step supports these parameters: { "description": str, # Required: Human-readable description "action": str, # Required: Action identifier "parameters": dict, # Required: Action parameters "expected_output": str, # Required: Expected result "safety_check": bool, # Optional: Enable validation (default: True) "rollback_possible": bool, # Optional: Can be rolled back (default: True) "max_retries": int # Optional: Retry attempts (default: 3) } ### API Orchestration steps = [ { "description": "Authenticate", "action": "api_auth", "parameters": {"service": "github"}, "expected_output": "Auth token" }, { "description": "Fetch data", "action": "api_fetch", "parameters": {"endpoint": "/repos"}, "expected_output": "Repository list" } ] ### Data Pipeline steps = [ { "description": "Extract data", "action": "extract", "parameters": {"source": "database"}, "expected_output": "Raw data" }, { "description": "Transform data", "action": "transform", "parameters": {"rules": ["normalize", "validate"]}, "expected_output": "Clean data" }, { "description": "Load data", "action": "load", "parameters": {"destination": "warehouse"}, "expected_output": "Success confirmation" } ] ### System Automation steps = [ { "description": "Backup database", "action": "backup", "parameters": {"target": "postgres"}, "expected_output": "Backup file path", "rollback_possible": True }, { "description": "Update schema", "action": "migrate", "parameters": {"version": "2.0"}, "expected_output": "Migration complete", "rollback_possible": True }, { "description": "Verify integrity", "action": "verify", "parameters": {"checks": ["all"]}, "expected_output": "All checks passed" } ] ### 1. Always Validate First is_valid, warnings = planner.validate_plan(plan) if not is_valid: print("Plan validation failed!") for warning in warnings: print(f" - {warning}") exit(1) ### 2. Use Descriptive Names # Good ✅ { "description": "Fetch active users from PostgreSQL production database", "action": "fetch_active_users_postgres_prod", ... } # Bad ❌ { "description": "Get data", "action": "get", ... } ### 3. Mark Dangerous Operations { "description": "Delete temporary files older than 30 days", "action": "cleanup_temp_files", "parameters": {"age_days": 30, "path": "/tmp"}, "safety_check": True, # ⚠️ Will trigger warnings "rollback_possible": False # ⚠️ Cannot undo! } ### 4. Test with Dry Run # Always test first success, results = planner.execute_plan(plan, my_executor, dry_run=True) if success: # Now run for real success, results = planner.execute_plan(plan, my_executor, dry_run=False) ### 5. Handle Errors Gracefully def safe_executor(action: str, parameters: dict): try: result = execute_action(action, parameters) return result except Exception as e: logging.error(f"Failed to execute {action}: {e}") raise # Re-raise to let planner handle it ### Auto-Approve for Automation # Skip manual approval for automated workflows planner = TaskPlanner(auto_approve=True) ### Checkpoint System # Checkpoints are automatically created for rollback-capable steps # Access checkpoint history checkpoints = planner.executor.checkpoint_stack ### Execution History # View execution history history = planner.executor.execution_history for entry in history: print(f"{entry['timestamp']}: {entry['step_id']} - {entry['status']}") ### Custom Validation Rules # Add custom validation to SafetyValidator planner.safety_validator.dangerous_operations.append('my_dangerous_op') planner.safety_validator.sensitive_paths.append('/my/sensitive/path') ### "Plan must be approved before execution" # Solution: Approve the plan first planner.approve_plan(plan, approved_by="admin") # Or use auto-approve mode planner = TaskPlanner(auto_approve=True) ### Safety validation warnings # Review warnings and ensure operations are intentional is_valid, warnings = planner.validate_plan(plan) for warning in warnings: print(warning) # If operations are safe, approve anyway if is_valid: # Still valid, just warnings planner.approve_plan(plan) ### Steps executing out of order # Ensure order values are sequential steps[0]['order'] = 1 steps[1]['order'] = 2 steps[2]['order'] = 3 ### File Structure task-planner-validator/ ├── task_planner.py # Main library ├── examples.py # Usage examples ├── test_basic.py # Test suite ├── README.md # Full documentation ├── QUICKSTART.md # Quick start guide ├── API.md # API reference ├── SKILL.md # This file └── LICENSE # MIT License ### Requirements Python 3.8 or higher No external dependencies! ### Testing # Run basic tests python test_basic.py # Run examples python examples.py # Both should show "✅ ALL TESTS PASSED" ### Getting Help 📖 Read full documentation in README.md 🚀 Check QUICKSTART.md for quick examples 📚 See API.md for complete API reference 💡 Browse examples.py for real code 🐛 Report issues on GitHub ### License MIT License - see LICENSE file ### Author cerbug45 GitHub: @cerbug45 ⭐ If you find this useful, star the repository on GitHub! ## Trust - Source: tencent - Verification: Indexed source record - Publisher: cerbug45 - Version: 0.1.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-04T01:20:30.731Z - Expires at: 2026-05-11T01:20:30.731Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/task-panner-validator) - [Send to Agent page](https://openagent3.xyz/skills/task-panner-validator/agent) - [JSON manifest](https://openagent3.xyz/skills/task-panner-validator/agent.json) - [Markdown brief](https://openagent3.xyz/skills/task-panner-validator/agent.md) - [Download page](https://openagent3.xyz/downloads/task-panner-validator)