Task Runner

Manage and track tasks and projects persistently with priorities, completion status, filtering, and secure markdown export across sessions.

Security Scan

The skill's code and runtime instructions match its stated purpose (a local task manager) and request no credentials or installs, but the export path validation is permissive (allows writing anywhere in the user's home) and could be tightened.

Purpose & Capability

The SKILL.md and the included Python script both implement a local task manager: adding/listing/completing tasks and exporting projects to Markdown. There are no unrelated dependencies, environment variables, or external endpoints requested.

Instruction Scope

Runtime instructions only invoke the local script and describe local file exports/storage. The code does not access environment variables, network, or arbitrary system state. However, exports are allowed to the entire home directory (with a small list of blocked filename patterns), which is broader than the 'workspace-only' expectation some users might have.

Install Mechanism

No install spec is provided (instruction-only skill plus a script). Nothing is downloaded or written during install, so there is minimal install-time risk.

Credentials

The skill requires no environment variables or credentials. The only filesystem access is to a single JSON DB under ~/.openclaw/workspace and to user-provided export paths.

Persistence & Privilege

The skill does not request permanent/always-on inclusion and does not modify other skills or global agent configuration. It persists only its own tasks DB at ~/.openclaw/workspace/tasks_db.json.

Assessment

This skill appears to do exactly what it claims: a local task tracker with a JSON DB and Markdown export. Before installing/using it, consider: (1) the export function allows writing anywhere in your home directory except for a short blacklist of filename patterns — if you want stronger safety, restrict exports to the workspace directory only; (2) review the blacklist (it omits some dotfiles and config locations like general .config or .bash_history) if you are concerned about accidental overwrites; (3) back up any important files you might overwrite and inspect ~/.openclaw/workspace/tasks_db.json if you care about what data the skill stores; (4) because the skill can be invoked autonomously by an agent (normal default), ensure you trust the agent prompts that would call export with user-supplied paths. If you want maximum safety, only export to files inside ~/.openclaw/workspace or /tmp.

Manage tasks and projects across sessions with persistent tracking.

Quick Start

Add a task

task_runner.py add "<description>" [project] [priority]

List all tasks

task_runner.py list

List tasks for a specific project

task_runner.py list "<project>"

Complete a task

task_runner.py complete <task_id>

Change task priority

task_runner.py priority <task_id> <low|medium|high>

Export project to markdown

task_runner.py export "<project>" "<output_file>"

Features

• Persistent storage - Tasks survive session restarts (stored in ~/.openclaw/workspace/tasks_db.json)
• Project organization - Group tasks by project for better organization
• Priority levels - low, medium (default), high
• Status tracking - pending vs completed with timestamps
• Flexible filtering - View all tasks or filter by project
• Markdown export - Export projects to clean markdown for sharing

Security

Path Validation (v1.0.1+)

The export function validates output paths to prevent malicious writes:

• ✅ Allowed: ~/.openclaw/workspace/, /tmp/, and home directory
• ❌ Blocked: System paths (/etc/, /usr/, /var/, etc.)
• ❌ Blocked: Sensitive dotfiles (~/.bashrc, ~/.ssh, etc.)

This prevents prompt injection attacks that could attempt to write to system files for privilege escalation.

Task Storage

The task storage is JSON-based and only writes to ~/.openclaw/workspace/tasks_db.json.

Usage Patterns

For multi-session projects

# Add experiment tasks
task_runner.py add "Setup development environment" "project-x" "high"
task_runner.py add "Write initial tests" "project-x" "medium"
task_runner.py add "Document API endpoints" "project-x" "low"

# List project progress
task_runner.py list "project-x"

# Complete tasks as you go
task_runner.py complete 1
task_runner.py complete 2

For autonomous agent workflows

Track your own tasks across sessions:

# Plan experiments
task_runner.py add "Build and publish skill" "income-experiments" "high"
task_runner.py add "Test content pipeline" "income-experiments" "medium"

# Update priorities based on learning
task_runner.py priority 2 "high"

# Export progress reports
task_runner.py export "income-experiments" "./progress-report.md"

For sprint planning

# Plan week's work
task_runner.py.py add "Build feature X" "sprint-5" "high"
task_runner.py.py add "Fix bug Y" "sprint-5" "high"
task_runner.py.py add "Update documentation" "sprint-5" "medium"

# Review progress
task_runner.py list "sprint-5"

# Export for standup
task_runner.py export "sprint-5" "./standup.md"

Task Priorities

Priority	Emoji	When to Use
high	🔴	Blocking issues, urgent, must do now
medium	🟡	Normal work, do soon
low	🟢	Nice to have, backlog items

Output Format

Task listing shows:

• Status icon (✅ completed, ⏳ pending)
• Project name
• Task ID number
• Priority emoji
• Creation date
• Task description
• Completion date (if completed)

Export Format

Markdown export includes:

• Project title with task counts
• Pending tasks section
• Completed tasks section (most recent first)
• Task IDs, priorities, and timestamps

Examples

Managing a coding project

# Setup
task_runner.py add "Clone repository" "my-project" "high"
task_runner.py add "Install dependencies" "my-project" "high"
task_runner.py add "Set up database" "my-project" "medium"

# Track progress
task_runner.py list "my-project"
task_runner.py complete 1
task_runner.py complete 2

# Export for documentation
task_runner.py export "my-project" "./my-project-tasks.md"

Tracking autonomous agent experiments

# Plan experiments
task_runner.py add "Experiment 1: Publish skills" "autonomous-income" "high"
task_runner.py add "Experiment 2: Content automation" "autonomous-income" "medium"
task_runner.py add "Experiment 3: Service MVP" "autonomous-income" "low"

# Work through them
task_runner.py list "autonomous-income"
task_runner.py complete 1

# Adjust based on learning
task_runner.py add "Experiment 2a: Research tools without API keys" "autonomous-income" "high"
task_runner.py priority 2 "low"

Daily task management

# Plan the day
task_runner.py add "Review pull requests" "daily" "high"
task_runner.py add "Write documentation" "daily" "medium"
task_runner.py add "Respond to emails" "daily" "low"

# End-of-day review
task_runner.py list

# Archive completed work
task_runner.py export "daily" "./$(date +%Y-%m-%d)-tasks.md"

Best Practices

1. Use meaningful project names - income-experiments not ideas
2. Set priorities consistently - helps with focus
3. Mark tasks complete promptly - keeps list clean
4. Export before major changes - backup progress
5. Review and clean up - archive old projects regularly

Integration with Other Skills

Combine with research-assistant for complete project management:

• Use research-assistant for notes and knowledge
• Use task-runner for actionable tasks
• Export both to create comprehensive project docs