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TaskWing
TaskWing

Give your AI tools a brain.

Memory, planning, task execution, and project intelligence — the control plane for AI-native development.

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TaskWing ask demo


The Problem

Your AI tools start every session from zero. They don't know your stack, your patterns, or why you chose PostgreSQL over MongoDB. You re-explain the same context hundreds of times.

TaskWing fixes this. One command extracts your architecture into a local database. Every AI session after that just knows.

Why TaskWing?

Your AI assistant reads the same files every session. TaskWing remembers so it doesn't have to.

Without TaskWing              With TaskWing
─────────────────             ─────────────
8–12 file reads               1 MCP query
~25,000 tokens                ~1,500 tokens
2–3 minutes                   42 seconds
Zero persistent context       170+ knowledge nodes

Real session, real numbers — asked "What are the bottlenecks in our engineering process?":

  • Without TaskWing: 8 Glob/Grep searches, 12 file reads, 25,000 tokens, 3 minutes
  • With TaskWing MCP: 1 query, 1,500 tokens, 42 seconds — synthesized answer with code references

That's 90% fewer tokens and 75% faster time-to-answer.

What It Does

Capability Description
🧠 Memory Extracts and persists architectural decisions, patterns, and constraints
📋 Planning Turns a goal into an executable plan with decomposed tasks
Task Execution AI-driven task lifecycle — next, start, complete, verify
🔍 Code Intelligence Symbol search, call graphs, impact analysis, simplification
🐛 Debugging AI-powered root cause analysis with systematic diagnosis
🔌 MCP Integration Exposes everything to Claude, Cursor, Copilot, Gemini via MCP

Install

# Homebrew (recommended)
brew install josephgoksu/tap/taskwing

# or curl
curl -fsSL https://taskwing.app/install.sh | sh

No signup. No account. Works offline. Everything stays local in SQLite.

Supported Models

OpenAI Anthropic Google Gemini AWS Bedrock Ollama

Works With

Claude Code OpenAI Codex Cursor GitHub Copilot Gemini CLI OpenCode

Brand names and logos are trademarks of their respective owners; usage here indicates compatibility, not endorsement.

Quick Start

# 1. Extract your architecture
cd your-project
taskwing bootstrap
# → 22 decisions, 12 patterns, 9 constraints extracted

# 2. Set a goal and generate a plan
taskwing goal "Add Stripe billing"
# → Plan decomposed into 5 executable tasks

# 3. Execute with your AI assistant
/taskwing:next       # Get next task with full context
# ...work...
/taskwing:done       # Mark complete, advance to next

MCP Tools

Tool Description
ask Search project knowledge (decisions, patterns, constraints)
task Unified task lifecycle (next, current, start, complete)
plan Plan management (clarify, decompose, expand, generate, finalize, audit)
code Code intelligence (find, search, explain, callers, impact, simplify)
debug Diagnose issues systematically with AI-powered analysis
remember Store knowledge in project memory

MCP Setup

Add to your AI tool's MCP config:

{
  "mcpServers": {
    "taskwing": {
      "command": "taskwing",
      "args": ["mcp"]
    }
  }
}

Slash Commands

Once connected, use these slash commands from your AI assistant:

Command When to use
/taskwing:ask Search project knowledge (decisions, patterns, constraints)
/taskwing:remember Persist a decision, pattern, or insight to project memory
/taskwing:next Start the next approved task with full context
/taskwing:done Complete the current task after verification
/taskwing:status Check current task progress and acceptance criteria
/taskwing:plan Clarify a goal and build an approved execution plan
/taskwing:debug Root-cause-first debugging before proposing fixes
/taskwing:explain Deep explanation of a code symbol and its call graph
/taskwing:simplify Simplify code while preserving behavior

Core Commands

  • taskwing bootstrap
  • taskwing goal "<goal>"
  • taskwing ask "<query>"
  • taskwing task
  • taskwing plan status
  • taskwing slash
  • taskwing mcp
  • taskwing doctor
  • taskwing config
  • taskwing start

Autonomous Task Execution (Hooks)

TaskWing integrates with Claude Code's hook system for autonomous plan execution:

taskwing hook session-init      # Initialize session tracking
taskwing hook continue-check    # Check if should continue to next task
taskwing hook session-end       # Cleanup session
taskwing hook status            # View current session state

Circuit breakers prevent runaway execution:

  • --max-tasks=5 — Stop after N tasks for human review
  • --max-minutes=30 — Stop after N minutes

AWS Bedrock Setup

TaskWing supports Bedrock as a first-class provider:

llm:
  provider: bedrock
  model: anthropic.claude-sonnet-4-5-20250929-v1:0
  bedrock:
    region: us-east-1
  apiKeys:
    bedrock: ${BEDROCK_API_KEY}
Recommended Bedrock models
Model Use case
anthropic.claude-opus-4-6-v1 Highest quality reasoning
anthropic.claude-sonnet-4-5-20250929-v1:0 Best default balance
amazon.nova-premier-v1:0 AWS flagship Nova
amazon.nova-pro-v1:0 Strong balance
meta.llama4-maverick-17b-instruct-v1:0 Open-weight general model

Or configure interactively: taskwing config

Documentation

License

MIT

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Memory, planning, task execution, and project intelligence for Claude Code, Codex and Gemini

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