# AI use cases for Argus Agent (microsoft/ArgusAgent)

Repo: [microsoft/ArgusAgent](https://github.com/microsoft/ArgusAgent) | Use cases: 4 | Page: https://dedupedai.com/use-cases/microsoft-argusagent/

Argus is a persistent multi-agent runtime that plans, executes, and reviews long-running research and engineering work across several coding agent backends.

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

- Run a multi-hour research or engineering campaign with review: https://dedupedai.com/use-cases/microsoft-argusagent/run-long-research-campaign-with-review/
- Search for mathematical counterexamples with the Counterexample Lab: https://dedupedai.com/use-cases/microsoft-argusagent/search-for-counterexamples-with-jacobian-lab/
- Benchmark the Argus runtime as a custom agent in Harbor: https://dedupedai.com/use-cases/microsoft-argusagent/evaluate-argus-as-a-harbor-agent/
- Add Argus tools to a coding agent you already use: https://dedupedai.com/use-cases/microsoft-argusagent/use-argus-tools-inside-coding-agent/

## How to run a multi-hour research or engineering campaign with review with Argus Agent

Repo: [microsoft/ArgusAgent](https://github.com/microsoft/ArgusAgent) | Difficulty: Intermediate | Time: 45 minutes | Basis: From the README

Start an Argus campaign that plans, executes, and reviews work without a human at the keyboard.

**Who it is for:** An engineer or researcher with a multi-stage project who needs progress to continue overnight or between meetings.

**The problem:** A single agent chat stops when the model turn ends, so long work needs someone to restart it and check each result.

**The outcome:** A campaign that keeps moving through stages, where a separate Reviewer must accept each result before it counts as done.

### Steps

1. Install Node.js 22.12 or later and sign in to one Agent CLI, for example by running `copilot login`.
2. Run `argus --config-help` to see the available configuration options.
3. Run `argus` and give it the goal and the project folder for the campaign.
4. Check progress at any time with `argus --status`.
5. When the campaign is finished or you want it to stop, run `argus --daemon-stop --drain`.

### Prompt to paste into your agent

```text
Using the microsoft/ArgusAgent repo, start an Argus campaign for the goal <research or engineering goal> in the folder <project path>. Expect the output of `argus --status` showing the current stage and the artifacts the Reviewer has accepted. Verify that any step involving credentials, payment, irreversible actions, or publication is paused for a human.
```

### Caveat

Setup, diagnostics, and tasks can use your provider's quota or paid usage, and the README says Argus is not a filesystem sandbox, so use a folder you can restore.

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/microsoft-argusagent/run-long-research-campaign-with-review/

## How to search for mathematical counterexamples with the Counterexample Lab with Argus Agent

Repo: [microsoft/ArgusAgent](https://github.com/microsoft/ArgusAgent) | Difficulty: Advanced | Time: 1 hour 30 minutes | Basis: From the README

Use the live Counterexample Lab and the Jacobian MCP bridge to run counterexample research through Argus.

**Who it is for:** A researcher testing a conjecture who wants an agent to propose and check candidate counterexamples.

**The problem:** Checking many candidate counterexamples by hand is slow, and the checks need a dedicated environment separate from ordinary code work.

**The outcome:** A set of candidate counterexamples checked in the Counterexample Lab, with the Reviewer's verdict on each result.

### Steps

1. Complete the basic install: Node.js 22.12 or later and one authenticated Agent CLI.
2. Open the setup guide at docs/counterexample-lab-jacobian.md and follow it to start the Counterexample Lab and the isolated Jacobian MCP bridge.
3. Run `argus` and describe the conjecture and the search space to the Planner.
4. Let the Engineer run the candidate checks and review the Reviewer's verdicts.
5. Use `argus --status` to confirm which candidates are verified and which are blocked.

### Prompt to paste into your agent

```text
Using the microsoft/ArgusAgent repo, set up the Counterexample Lab from docs/counterexample-lab-jacobian.md and search for counterexamples to the conjecture <conjecture statement>. Expect a list of candidate counterexamples with a Reviewer verdict for each. Verify that every reported counterexample was checked by the lab, not only proposed by the model.
```

### Caveat

The Jacobian bridge and lab setup live in a separate guide, so the steps here depend on that document, which this summary did not read in full.

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/microsoft-argusagent/search-for-counterexamples-with-jacobian-lab/

## How to benchmark the Argus runtime as a custom agent in Harbor with Argus Agent

Repo: [microsoft/ArgusAgent](https://github.com/microsoft/ArgusAgent) | Difficulty: Advanced | Time: 2 hours | Basis: From the README

Run the full Argus Manager, Planner, Engineer and Reviewer runtime inside Harbor Framework for evaluation.

**Who it is for:** An evaluation engineer who needs to compare Argus against other agents on the same Harbor tasks.

**The problem:** Comparing agent systems fairly requires running each one through the same harness, and Argus is not wired into Harbor by default.

**The outcome:** Harbor results that record how the bounded Argus runtime performed on the chosen tasks.

### Steps

1. Install Docker, which the README lists as required only for the Harbor integration.
2. Complete the basic Argus install with Node.js 22.12 or later and one authenticated Agent CLI.
3. Open the Harbor integration guide at docs/harbor.md.
4. Register Argus as a custom agent in Harbor by following that guide.
5. Run your Harbor task set and read the results alongside the Argus status output.

### Prompt to paste into your agent

```text
Using the microsoft/ArgusAgent repo, follow docs/harbor.md to run the Argus runtime as a custom agent in Harbor Framework on the task set <task set name>. Expect Harbor's result report for each task. Verify that the runtime ran in its bounded form and that each task result links back to its Argus run.
```

### Caveat

The README describes Harbor as a separate integration, so it is not part of a normal Argus install and needs its own guide.

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/microsoft-argusagent/evaluate-argus-as-a-harbor-agent/

## How to add Argus tools to a coding agent you already use with Argus Agent

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

Connect the packaged MCP bridge and host-specific Skills to your coding agent without changing the core runtime.

**Who it is for:** A developer who works mainly in one coding agent and wants Argus's capabilities available from that host.

**The problem:** Switching to a separate Argus workflow interrupts the coding agent you already trust and use every day.

**The outcome:** Your existing coding agent can call Argus tools through the MCP bridge and the Skills for its host.

### Steps

1. Complete the basic install with Node.js 22.12 or later and sign in to your coding agent CLI.
2. Open the plugin quick start at docs/plugin.md.
3. Install the packaged MCP bridge and the Skills that match your host, as the guide describes.
4. Restart your coding agent so it loads the new bridge and Skills.
5. Ask the agent to use an Argus tool on a small task in a test folder and check the result.

### Prompt to paste into your agent

```text
Using the microsoft/ArgusAgent repo, follow docs/plugin.md to connect the packaged MCP bridge and host-specific Skills to <your coding agent host>. Expect the host to list the Argus tools after restart. Verify that a small test task in an empty folder completes and that the core Argus runtime files were not changed.
```

### Caveat

The exact bridge and Skill installation steps are in docs/plugin.md, which this summary did not read in full, so confirm the host names it supports there.

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/microsoft-argusagent/use-argus-tools-inside-coding-agent/