GraphCanon updated 6d · GitHub synced 6d
Decision brief
Waggle-dance is an AI-driven knowledge work automation tool built in TypeScript with experimental concurrent agent execution for faster task resolution.
Good fit when
- You need a system that prioritizes speed and concurrency in executing tasks
- You prefer a TypeScript project over Python alternatives in the same category
Avoid when
- Your project demands high stability over experimental features
- You require extensive customization of agent execution behavior beyond what Waggle-dance offers initially
Observed Jul 14, 2026 · Source: enrich:decision_facts
Verify the decision
Adoption
Package downloads where a registry match exists. GitHub stars (171) are secondary evidence.
- npm downloads (30d)
- 28·npm downloads API·6d
Maintenance and security
Full trust report- Maintenance
- Archived (971d since push)
- As of 6d
- Provenance
- Not a fork · Organization account
- As of 6d
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install waggle-danceSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Automates knowledge work using an agent-based framework that includes Planner Agents, Execution Agents, and Criticism Agents to achieve user-specified goals.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 15, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 15, 2026
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Aug 15, 2026
- MCP server
- No MCP server detected
Source: repo_scan · Aug 15, 2026
- Languages
- typescript, javascript
Source: github.language+package.json · Aug 15, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 15, 2026)
ity_, and _simplicity_. Additionally, many other agentic systems are written in Python, so this project acts as a small counter-balance, and is accessible to the largSource link
Tags
README
Quick Start
- Try the cloud preview ↗
- Join the Discord
- ⭐️ Help with algorithm: star this repo
You can also build and deploy yourself! However, you must configure your environment.
Deploy to Vercel
- Docker Compose
- Build and run from source
waggledance.ai is an experimental application focused on achieving user-specified goals. It provides a friendly but opinionated user interface for building agent-based systems. The project focuses on explainability, observability, concurrent generation, and exploration. Currently in pre-alpha, the development philosophy prefers experimentation over stability as goal-solving and Agent systems are rapidly evolving.
waggledance.ai takes a goal and passes it to a Planner Agent which streams an execution graph for sub-tasks. Each sub-task is executed as concurrently as possible by Execution Agents. To reduce poor results and hallucinations, sub-results are reviewed by Criticism Agents. Eventually, the Human in the loop (you!) will be able to chat with individual Agents and provide course-corrections if needed.
It was originally inspired by Auto-GPT, and has concurrency features similar to those found in gpt-researcher. Therefore, core tenets of the project include speed, accuracy, observability, and simplicity. Additionally, many other agentic systems are written in Python, so this project acts as a small counter-balance, and is accessible to the large number of Javascript developers.
An (unstable) API is also available via tRPC as well an API implemented within Next.js. The client-side is mostly responsible for orchestrating and rendering the agent executions, while the API and server-side executes the agents and stores the results. This architecture is likely to be adjusted in the future.
For agents
This page has a .md twin and JSON over the API.