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Task Panner Validator

Task Planner and Validator Skill Guide

cerbug450 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

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skillhub install cerbug45/task-panner-validator

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Skill instructions

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

Basic Usage

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']}%")

Key Features

Safety Validation

Automatically detects dangerous operatio...

Source information

Source
github
Repository
openclaw/skills
Path
skills/cerbug45/task-panner-validator
Version
—
Commit
c0fee08eb8a8a92e33fc9c2575abfa04fc2a9c35
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

Task Planner and Validator

A secure, step-by-step task management system designed for AI Agents to safely plan, validate, and execute complex multi-step tasks.

License: MIT Python 3.8+

🎯 Features

  • ✅ Step-by-Step Planning: Break down complex tasks into manageable, ordered steps
  • 🔒 Safety Validation: Built-in security checks for dangerous operations
  • 🔄 Rollback Support: Checkpoint system for reverting failed operations
  • 📝 Plan Persistence: Save and load plans in JSON format
  • 🎨 Integrity Verification: SHA-256 checksums to prevent tampering
  • ⚡ Execution Control: Dry-run mode, auto-approve, and stop-on-error options
  • 📊 Progress Tracking: Real-time status updates and execution summaries
  • 🔍 Detailed Logging: Comprehensive logging for debugging and auditing

🚀 Quick Start

Installation
# Clone the repository
git clone https://github.com/cerbug45/task-planner-validator.git
cd task-planner-validator

# No additional dependencies required - uses only Python standard library!
Basic Usage
from task_planner import TaskPlanner

# Create a planner
planner = TaskPlanner(auto_approve=False)

# Define your steps
steps = [
    {
        "description": "Fetch user data from API",
        "action": "fetch_data",
        "parameters": {"endpoint": "/api/users", "method": "GET"},
        "expected_output": "List of user objects",
        "safety_check": True,
        "rollback_possible": True
    },
    {
        "description": "Process and validate data",
        "action": "process_data",
        "parameters": {"validation_rules": ["email", "age"]},
        "expected_output": "Validated user data",
        "safety_check": True,
        "rollback_possible": True
    }
]

# Create a plan
plan = planner.create_plan(...

Extracted content

SKILL.md
# Task Planner and Validator - Skill Guide

This skill provides a secure, step-by-step task management system for AI Agents.

## Quick Installation

```bash
# 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

```bash
# Run tests
python test_basic.py

# Run examples
python examples.py
```

## Basic Usage

### 1. Import and Initialize

```python
from task_planner import TaskPlanner

# Create planner
planner = TaskPlanner(auto_approve=False)
```

### 2. Define Your Executor

```python
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

```python
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

```python
# 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']}%")
```

## Key Features

### Safety Validation

Automatically detects dangerous operatio...
README
# Task Planner and Validator

A secure, step-by-step task management system designed for AI Agents to safely plan, validate, and execute complex multi-step tasks.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)

## 🎯 Features

- **✅ Step-by-Step Planning**: Break down complex tasks into manageable, ordered steps
- **🔒 Safety Validation**: Built-in security checks for dangerous operations
- **🔄 Rollback Support**: Checkpoint system for reverting failed operations
- **📝 Plan Persistence**: Save and load plans in JSON format
- **🎨 Integrity Verification**: SHA-256 checksums to prevent tampering
- **⚡ Execution Control**: Dry-run mode, auto-approve, and stop-on-error options
- **📊 Progress Tracking**: Real-time status updates and execution summaries
- **🔍 Detailed Logging**: Comprehensive logging for debugging and auditing

## 🚀 Quick Start

### Installation

```bash
# Clone the repository
git clone https://github.com/cerbug45/task-planner-validator.git
cd task-planner-validator

# No additional dependencies required - uses only Python standard library!
```

### Basic Usage

```python
from task_planner import TaskPlanner

# Create a planner
planner = TaskPlanner(auto_approve=False)

# Define your steps
steps = [
    {
        "description": "Fetch user data from API",
        "action": "fetch_data",
        "parameters": {"endpoint": "/api/users", "method": "GET"},
        "expected_output": "List of user objects",
        "safety_check": True,
        "rollback_possible": True
    },
    {
        "description": "Process and validate data",
        "action": "process_data",
        "parameters": {"validation_rules": ["email", "age"]},
        "expected_output": "Validated user data",
        "safety_check": True,
        "rollback_possible": True
    }
]

# Create a plan
plan = planner.create_plan(...

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