# AI use cases for Tab Tin (tabtin-ai/TabTin)

Repo: [tabtin-ai/TabTin](https://github.com/tabtin-ai/TabTin) | Use cases: 4 | Page: https://dedupedai.com/use-cases/tabtin-ai-tabtin/

TabTin is an open source workspace where people and multiple AI agents share tasks, context, documents, and results.

This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL.

- Run Tab Tin from source on your own machine: https://dedupedai.com/use-cases/tabtin-ai-tabtin/run-tabtin-from-source-with-an-agent/
- Hand off an AI task with its context to a colleague: https://dedupedai.com/use-cases/tabtin-ai-tabtin/hand-off-a-task-with-its-context/
- Turn agent results into shared online documents and sheets: https://dedupedai.com/use-cases/tabtin-ai-tabtin/share-agent-output-as-online-documents/
- Reuse verified research and review methods across agent roles: https://dedupedai.com/use-cases/tabtin-ai-tabtin/reuse-verified-team-agent-methods/

## How to run Tab Tin from source on your own machine with Tab Tin

Repo: [tabtin-ai/TabTin](https://github.com/tabtin-ai/TabTin) | Difficulty: Intermediate | Time: 1 hour | Basis: From the README

Clone the repo and start the quick or full local preview with a coding agent or by hand.

**Who it is for:** A developer or power user who wants to try, debug, or modify Tab Tin locally instead of using the official service.

**The problem:** Setting up the many local tools and services that Tab Tin needs is slow and easy to get wrong.

**The outcome:** A local Tab Tin preview running, with the backend health check passed and the Electron window ready.

### Steps

1. Ask a coding agent to check and install Node.js, pnpm, Python, Go, Git, Docker, and Docker Compose by following docs/development/community-dev-agent-prompt.md.
2. Run `cp .env.example .env` in the repo root. This copies the template only and does not overwrite existing local files.
3. Run `node scripts/dev.mjs community` for the quick preview (Community backend and Electron), or `pnpm dev` for the full preview.
4. Wait for the backend health check and the Electron window, then stop all processes with Ctrl+C.

### Prompt to paste into your agent

```text
Run the quick preview of the TabTin repo at <local-clone-path> by following docs/development/community-dev-agent-prompt.md. Report whether the backend health check passed and whether the Electron window is ready, and confirm that the root .env file is not staged for commit.
```

### Caveat

The README says the local source run is a development entry point, not a Community distribution package or formal Release build, and Android and iOS Debug builds must be built separately.

Risk, credentials: The root .env and .env.local files hold local switches, including an optional fixed verification code setting, and the README says neither file may be committed.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/tabtin-ai-tabtin/run-tabtin-from-source-with-an-agent/

## How to hand off an AI task with its context to a colleague with Tab Tin

Repo: [tabtin-ai/TabTin](https://github.com/tabtin-ai/TabTin) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README

Freeze the needed context and files so a teammate can continue the work in their own task.

**Who it is for:** A team member who has finished part of a research or delivery task with an agent and must pass it to someone else.

**The problem:** Handoffs usually lose the reasoning behind a conclusion, so the next person repeats the research.

**The outcome:** The colleague opens a separate task that carries the frozen conversation context and the shared files, and can see how the conclusion was formed.

### Steps

1. Open the finished task at https://tabtin.com/ or in your Tab Tin client.
2. Start a task continuation so the necessary conversation context is frozen.
3. Attach the documents, sheets, cloud files, and local files referenced in the task that you have the right to share.
4. Send the continuation to the colleague, who creates an independent task in their chosen Agent and Workspace and continues from it.

### Prompt to paste into your agent

```text
Read the README at <repo-path>/README.md, section 工作可以交接, and list what a task continuation carries and what stays local to each person. Report any item that the README does not state, and do not claim features beyond it.
```

### Caveat

The README says each person's local files and execution environment stay separate, so the recipient must still have the local files they need before continuing.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/tabtin-ai-tabtin/hand-off-a-task-with-its-context/

## How to turn agent results into shared online documents and sheets with Tab Tin

Repo: [tabtin-ai/TabTin](https://github.com/tabtin-ai/TabTin) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Have agents write into Tab Tin documents, sheets, and slides so people edit the same result.

**Who it is for:** A team lead or analyst who needs agent research to become a document, spreadsheet, or slide deck that colleagues can edit.

**The problem:** Agent output often gets copied between chat windows, downloads, and office software, which creates version drift.

**The outcome:** A shared online document, multi-dimensional sheet, or presentation that both the agent and team members work on directly.

### Steps

1. Sign in at https://tabtin.com/ or open your Tab Tin client.
2. Ask an agent to create or edit a document, multi-dimensional sheet, or presentation in the collaboration apps.
3. Send browser-captured data and media into the work apps so they sit next to the agent result.
4. Share the item with teammates, who review and edit the same online result without moving files.

### Prompt to paste into your agent

```text
Read the README at <repo-path>/README.md, section 人和 Agent 操作同一份结果, and list the collaboration apps it names. Report which apps are named and flag any app mentioned in your own notes that the README does not name.
```

### Caveat

The README describes these apps at a high level, so check the current official service for exact editing limits before relying on them for a specific workflow.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/tabtin-ai-tabtin/share-agent-output-as-online-documents/

## How to reuse verified research and review methods across agent roles with Tab Tin

Repo: [tabtin-ai/TabTin](https://github.com/tabtin-ai/TabTin) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Store research, review, test, and release rules in agent roles so later tasks reuse them.

**Who it is for:** A team lead who wants proven agent workflows to survive staff changes instead of living in one person's prompt.

**The problem:** Good methods stay in one member's private prompt, so the team repeats trial and error.

**The outcome:** Agent roles with their own rules, models, Skills, and memory that apply the team's verified methods to new tasks, with a human still signing off on results.

### Steps

1. Create one agent role per recurring job, such as research, review, testing, or release.
2. Configure each role with its rules, model, Skill, and memory, using the team's verified steps.
3. Assign new tasks to the matching role so they reuse the stored method.
4. Have a person review the result and confirm responsibility before the output is accepted.

### Prompt to paste into your agent

```text
Read the README at <repo-path>/README.md, section 团队方法可以复用, and list which elements an agent role can be configured with. Report what the README says about human review, and do not add features it does not describe.
```

### Caveat

The README says the configurable roles, Skills, and memory are described as partly default implementations that are still being improved, so verify each role's behavior on a test task first.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/tabtin-ai-tabtin/reuse-verified-team-agent-methods/