# AI use cases for Frontier Agent (ApodexAI/FrontierAgent)

Repo: [ApodexAI/FrontierAgent](https://github.com/ApodexAI/FrontierAgent) | Use cases: 4 | Page: https://dedupedai.com/use-cases/apodexai-frontieragent/

FrontierAgent is an open-source agent runtime and terminal app (the frontier-agent TUI) with ReAct and Agent Team workflows for long-horizon research and file-based work.

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

- Research a question with a parallel agent team: https://dedupedai.com/use-cases/apodexai-frontieragent/research-question-with-agent-team/
- Analyze a project or documents with one stateful agent: https://dedupedai.com/use-cases/apodexai-frontieragent/analyze-project-files-with-react/
- Install frontier-agent once and launch it in any folder: https://dedupedai.com/use-cases/apodexai-frontieragent/install-frontier-agent-once-for-any-project/
- Run the agent in a Docker container from a local build: https://dedupedai.com/use-cases/apodexai-frontieragent/run-agent-in-docker-with-local-build/

## How to research a question with a parallel agent team with Frontier Agent

Repo: [ApodexAI/FrontierAgent](https://github.com/ApodexAI/FrontierAgent) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

A coordinator splits a broad question into parallel sub-agent tasks and returns one synthesized report.

**Who it is for:** A researcher or analyst with a broad question that needs several sources checked at once.

**The problem:** One agent working alone checks sources one at a time, which is slow for broad questions with many angles.

**The outcome:** A final report built from structured sub-agent findings, with deliverables and the run trace saved in the run directory.

### Steps

1. `git clone https://github.com/ApodexAI/FrontierAgent.git`
2. `cd FrontierAgent`
3. `uv sync --python 3.12 --extra dev`
4. `cp .env.example .env`, then set OPENAI_API_KEY, OPENAI_BASE_URL, and OPENAI_MODEL in .env
5. `uv run frontier-agent --mode agent_team --cwd /path/to/project "Research the alternatives, verify the evidence, and write a report"` (inferred, check the README)

### Prompt to paste into your agent

```text
Using the FrontierAgent repo at <repo path>, run agent_team mode with --cwd set to <project path> and the question <question>. The expected output is a final report plus deliverables in the run's /outputs folder. Verify that the report cites evidence the sub-agents collected and that the run directory contains the checkpoint and trace.
```

### Caveat

Agent Team sub-agents run in parallel on top of benchmark concurrency, so total model calls can grow quickly; the README advises starting with --concurrency 1 when evaluating.

Risk, credentials: Your model API key goes into the .env file, so keep that file out of shared repositories and screenshots.

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/apodexai-frontieragent/research-question-with-agent-team/

## How to analyze a project or documents with one stateful agent with Frontier Agent

Repo: [ApodexAI/FrontierAgent](https://github.com/ApodexAI/FrontierAgent) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

A single ReAct agent reads files, runs commands, and writes deliverables inside a sandboxed task folder.

**Who it is for:** A developer or analyst who wants a focused explanation of a codebase or a set of documents.

**The problem:** Reading an unfamiliar repository or a stack of documents by hand takes time, and general chat tools cannot touch local files.

**The outcome:** A focused answer about the target files, with any written deliverables kept in the run's /outputs folder.

### Steps

1. `git clone https://github.com/ApodexAI/FrontierAgent.git`
2. `uv sync --python 3.12 --extra dev`
3. `cp .env.example .env`, then set your endpoint values in .env
4. `uv run frontier-agent --mode react --cwd /path/to/project -p "explain src/main.py"` (inferred, check the README)
5. `uv run frontier-agent --mode react --cwd /repo --input ~/Downloads/claim.pdf --input ~/Desktop/photo.jpg` (inferred, check the README)

### Prompt to paste into your agent

```text
Using the FrontierAgent repo at <repo path>, run react mode with --cwd set to <target folder> and attach the documents <document paths> with --input. The expected output is a written summary of the files in /outputs. Verify that the agent only reads from /inputs and that each command it ran appears in the trace.
```

### Caveat

Mutating operations show a diff and need approval unless --yes is enabled, so review each change before you approve it.

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/apodexai-frontieragent/analyze-project-files-with-react/

## How to install frontier-agent once and launch it in any folder with Frontier Agent

Repo: [ApodexAI/FrontierAgent](https://github.com/ApodexAI/FrontierAgent) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Install the command with uv and keep your endpoint settings in one user file.

**Who it is for:** A developer who works across several project folders and wants one launch command everywhere.

**The problem:** Cloning the repo and setting up the environment for each project is repetitive and easy to get wrong.

**The outcome:** A frontier-agent command that starts the TUI from any project directory using your saved endpoint settings.

### Steps

1. `uv tool install --python 3.12 git+https://github.com/ApodexAI/FrontierAgent.git`
2. Put OPENAI_API_KEY, OPENAI_BASE_URL, and OPENAI_MODEL into ${XDG_CONFIG_HOME:-$HOME/.config}/apodex/env, then run `chmod 600` on that file
3. `cd /path/to/project`
4. `frontier-agent`

### Prompt to paste into your agent

```text
Install the FrontierAgent command from the repo at git+https://github.com/ApodexAI/FrontierAgent.git, then start it inside <project path>. The expected output is an open TUI session scoped to that project. Verify that the endpoint settings load from the user config file and that the session starts without errors.
```

### Caveat

On macOS with Docker running, the container image has to be built once from a clone before this command runs as expected.

Risk, credentials: The API key is stored in a plain user file, so restrict its permissions and never commit it to version control.

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/apodexai-frontieragent/install-frontier-agent-once-for-any-project/

## How to run the agent in a Docker container from a local build with Frontier Agent

Repo: [ApodexAI/FrontierAgent](https://github.com/ApodexAI/FrontierAgent) | Difficulty: Advanced | Time: 45 minutes | Basis: From the README

Build the checkout into a container with Compose and run the agent inside it.

**Who it is for:** A team that prefers containerized runs of the agent over a native Python install.

**The problem:** Installing Python tooling on shared machines can conflict with other projects and makes setups hard to reproduce.

**The outcome:** The agent runs in a container built from your checkout, with the same TUI workflows available.

### Steps

1. `git clone https://github.com/ApodexAI/FrontierAgent.git`
2. `cd FrontierAgent`
3. `cp .env.example .env`, then set your endpoint values in .env
4. `docker compose -f compose.yaml -f compose.dev.yaml build`
5. `docker compose -f compose.yaml -f compose.dev.yaml run --rm agent`

### Prompt to paste into your agent

```text
Using the FrontierAgent repo at <repo path>, build the checkout with Docker Compose using compose.yaml and compose.dev.yaml, then run the agent service. The expected output is a running agent session inside the container. Verify that the container starts, reads the endpoint values from .env, and that the run directory is created.
```

### Caveat

The pre-built images on GitHub Container Registry are private, so this local build from a checkout is the path the README describes for most users.

Risk, credentials: The .env file with your API key is passed into the container build context, so check your .dockerignore before sharing images.

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/apodexai-frontieragent/run-agent-in-docker-with-local-build/