DEDUPEDWhat do you want to do?
4 use cases
-
Try the guided demo before connecting anything
Run Taskuary's fictional demo to see a request go from email to approved reply.
- REPO
ldbumble/taskuary - Work and operations
- Intermediate
View prompt
In the ldbumble/taskuary repo, install the package with `pip install taskuary` and start it with `taskuary --demo`. Report the title of the first task the Assistant shows, and confirm that the demo cannot send messages or start agents. Verify the demo output by checking that the task names fictional data only.
- REPO
-
Turn work mail into tasks you approve before anything sends
Connect a mail or chat channel, let an agent draft a reply, and approve it yourself.
View prompt
Use the ldbumble/taskuary repo to set up a local instance with `pip install taskuary` and `taskuary`, then connect the inbound channel <channel-name>. Report the task created from one incoming request and the state of its prepared reply. Verify that the reply is still unsent until the owner chooses Approve & send.
-
Run Taskuary as a Docker web app with coding CLIs on the host
Start the Taskuary web app in Docker while your coding CLIs stay on the host machine.
View prompt
Clone ldbumble/taskuary, run `docker compose up` in the repo folder, and report whether http://127.0.0.1:7787 responds. Verify that the coding CLIs are still installed on the host and not inside the container, as the README states.
-
Hand work from one coding agent to the next with shared notes
Use Taskuary's handoff board so each agent reads the last agent's note before continuing.
View prompt
In the ldbumble/taskuary repo, start the app with `taskuary`, send <task-title> to the first agent profile, and report the note it leaves in Live handoffs. Verify that the next agent profile reads that note before it starts its work.
Quick start with Taskuary
- Check you have what it needs: Python 3.10 or newer, or the Windows Taskuary.exe download, or Docker; An AI provider key or a local Ollama model; At least one inbound channel such as mail, chat or tickets.
- Open ldbumble/taskuary on GitHub and read the README and license.
- Install Python 3.10 or newer on Windows, macOS or Linux.
- Run
pip install taskuary - Run
taskuary --demo - Open http://127.0.0.1:7787 and choose Walk me through my tasks.
These steps come from our top use case, Try the guided demo before connecting anything, which also has a copy-paste agent prompt.
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About this repo
- Who it is forKnowledge workers who handle a steady flow of email, chat and ticket requests, and developers who want a local approval gate in front of their coding agents.
- Why it is hot143 stars, launched 70 days ago
- LanguagePython
- Sourcegithub.com/ldbumble/taskuary · Back to Hot repos
Requirements
- Python 3.10 or newer, or the Windows Taskuary.exe download, or Docker
- An AI provider key or a local Ollama model
- At least one inbound channel such as mail, chat or tickets
- A coding CLI such as Claude Code, Codex or Gemini if you want agents to do the work
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Questions about Taskuary
What is Taskuary?
Taskuary is an open source Python app that runs on your machine and turns mail, chats and tickets into tasks that coding agents work on, with nothing sent until you approve. It is an open-source project on GitHub: https://github.com/ldbumble/taskuary.
How do I use Taskuary?
Install Python 3.10 or newer on Windows, macOS or Linux; then run pip install taskuary; run taskuary --demo. The use cases on this page give the full steps and a copy-paste agent prompt for each job.
Who is Taskuary for?
Knowledge workers who handle a steady flow of email, chat and ticket requests, and developers who want a local approval gate in front of their coding agents.
What can I do with Taskuary?
4 use cases so far, for example: Try the guided demo before connecting anything; Turn work mail into tasks you approve before anything sends; Run Taskuary as a Docker web app with coding CLIs on the host. Each has steps and a copy-paste agent prompt.
What do I need to run Taskuary?
Python 3.10 or newer, or the Windows Taskuary.exe download, or Docker; An AI provider key or a local Ollama model; At least one inbound channel such as mail, chat or tickets; A coding CLI such as Claude Code, Codex or Gemini if you want agents to do the work.
What are alternatives to Taskuary?
Other hot AI repos in Work and operations: Solidcraft, Browser Use, Next AI Draw.io, Pilot Deck, OpenDots.
Is Taskuary safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.