Build a GitHub Copilot-style coding agent
~25 min TypeScript PythonWhat you’re building: An agent that takes an issue, works, and opens a PR.
Primitives you’ll use: Sandbox, Agent and harness
Agent prompt
Start with your coding agent
Choose what you are building. The brief names the product it is modelled on, maps it onto MIOSA, and lists the exact commands. Copy it into OSA, Claude Code, Codex, or Cursor.
Template coming soon1 What are you building?
Leave it empty and your agent will propose 3 names, pick one, and use it for resources, the domain and branding.
3 Configure
Reference product
GitHub Copilot coding agent, by GitHub (https://github.com/features/copilot): a coding agent that takes an issue, works in its own environment and opens a pull request.
How it works: You assign an issue to the agent; it works in an isolated environment, pushes commits to a branch and opens a pull request for review.
Key capabilities:
Assign an issue to an agent
Works in an isolated environment
Pushes commits and opens a pull request
Responds to review comments
Build an app LIKE GitHub Copilot coding agent. It is not affiliated with GitHub: do not copy its name, branding or assets. Open https://github.com/features/copilot first, confirm the capabilities above, and note anything this brief missed.
How it maps onto MIOSA
A workspace the agent can break safely -> a MIOSA sandbox per task, with the repo cloned into /workspace
The agent edits files and runs commands -> agent runs (`miosa prompt`, client.runs) streaming events on that sandbox (`miosa prompt --sandbox ... --harness ...`)
Parallel tasks -> one sandbox per task or branch, sandbox snapshots and fork to try a second approach
Results you can review -> `miosa run files`, `miosa run outputs`, and the git diff inside the sandbox
Issue in, pull request out -> git clone, branch, commit and push inside the sandbox using a repo-scoped token, then open the PR with your Git host API
Goal
Build an app like GitHub Copilot coding agent on MIOSA, as a multi-tenant product sold to my customers. Each customer is isolated in its own workspace; I meter usage and bill them.
Product name: propose 3 product names, pick one, and use it for resource names, the domain and branding. Until you pick, <product-name> stands for it in the commands below.
Scale: a prototype.
Set up
npm i -g @miosa/cli
miosa login && miosa whoami
miosa api-key create <product-name>-key --preset agent
export MIOSA_API_KEY="msk_u_..."
miosa org
miosa connections add models # your own model provider key
Resources
Sandbox: the agent's isolated Linux workspace
miosa create <product-name>-task-1 --wait
Agents and harnesses: what a run can use
miosa agent harnesses
Data and storage
Keep a tasks table in your own datastore: task id, repo, branch, sandbox id, run id, status, result links, and the user or customer it belongs to. The code itself lives in the sandbox and in Git, not in your database.
Nothing else needs storage: Git is the system of record for the code.
Auth and tenancy
Your organization is the platform; customers never get a MIOSA account, they sign into YOUR product. One workspace per customer, created as they onboard, isolates their machines, runs and data.
miosa workspace create <product-name>-customer-1
Tag every machine and run with the customer id in `metadata`, and never query across customers. Meter usage per customer with GET /api/v1/usage and set who pays with PUT /api/v1/bill-to (/docs/platform/usage-and-billing).
Agent loop
Harness: OSA is MIOSA's own harness and works with any model provider you connect, including your own model.
Model: Anthropic (Claude). Calls use my own provider key (`miosa connections add models`); MIOSA platform keys are never used.
Sessions: one chat per project or conversation, so the agent keeps its context. The first `miosa prompt` on a sandbox uses `--new-chat` (a chat id is printed); every later turn passes `--chat <chat-id>`. `--reuse chat` keeps one new machine per chat so files persist.
Streaming: follow a run with `miosa run follow <run-id>` or client.runs.streamEvents(run.id), and steer or stop it with `miosa run steer` and `miosa run interrupt`.
The harness runs headless INSIDE the task sandbox with the repo checked out. It edits files, runs the project's own commands and commits; you never apply its edits from outside.
Parallel sessions are separate sandboxes (and separate chats). Snapshot before a risky change and fork to try a second approach.
Steps
1. Create one sandbox per task or branch so parallel tasks never share state.
miosa create <product-name>-task-1 --size medium --wait
Check: The sandbox is running; two tasks have two sandboxes.
2. Clone the repository and create the task branch. Pass the Git token per exec or through the Secrets API; do not store it in the sandbox `env`.
miosa exec <product-name>-task-1 -- git clone <repo-url> /workspace/repo
miosa exec <product-name>-task-1 --cwd /workspace/repo -- git checkout -b task/<task-id>
Check: The repo is in /workspace/repo on the task branch.
3. Dispatch the harness with the task.
miosa prompt --sandbox <product-name>-task-1 --harness osa --model <anthropic-model-id> --chat <chat-id> "Resolve issue <number>; run the tests; commit your work"
Check: `miosa run list --status running` shows the run and events start streaming.
4. Follow the run, and steer or stop it from your UI.
miosa run follow <run-id>
miosa run steer --sandbox <product-name>-task-1 "also add tests"
miosa run interrupt --sandbox <product-name>-task-1
Check: The UI shows live events; a steer lands on the next turn; interrupt stops the agent.
5. Verify independently of the agent: run the test command yourself.
miosa exec <product-name>-task-1 --cwd /workspace/repo -- npm test
Check: Tests exit 0 in the sandbox, not just in the agent's summary.
6. Hand back a pull request: push the branch and open the PR with your Git host API, linking the MIOSA run id in the description.
miosa run files <run-id>
miosa run download <run-id> <file-id> --output ./result
miosa exec <product-name>-task-1 --cwd /workspace/repo -- git push origin task/<task-id>
Check: The diff is reviewable outside the sandbox and the run id is attached to it.
7. Close out. For one-shot tasks let MIOSA do it (`miosa prompt --new-machine ... --after-run destroy`); keep or snapshot the sandbox when the user may continue.
Check: No orphaned sandboxes remain after the task is closed.
Limits and costs
Set `--max-time` on every run so a stuck agent cannot run forever; use `--notify-email` or a webhook for long tasks.
Give the agent a token scoped to one repository, and only the permissions the task needs.
Parallel tasks multiply cost: cap concurrency per user or customer.
Prototype: keep it to one machine at the default size, skip replicas and custom hostnames you do not need, and delete everything when you are done.
Acceptance checks
Two tasks run at the same time in two sandboxes without touching each other.
A finished task leaves a reviewable branch or diff and the run id.
Nothing was deployed or published: the deliverable is the diff.
Each customer is isolated in its own workspace and usage is metered against them.
Everything it created can be deleted with nothing left running.
What your choices added
- Build a product. a workspace per customer, per-customer metering and bill-to
- Agent suggests a name. proposes 3 product names and picks one; commands use <product-name>
- Harness: OSA. dispatches with `miosa prompt --harness osa`
- Model: Anthropic. your own provider key
- Prototype. one small machine, no extras, easy to delete
What you're building
a coding agent that takes an issue, works in its own environment and opens a pull request Modelled on GitHub Copilot coding agent, by GitHub.
You assign an issue to the agent; it works in an isolated environment, pushes commits to a branch and opens a pull request for review.
Primitives you'll use: Sandbox · Agent and harness
- Assign an issue to an agent
- Works in an isolated environment
- Pushes commits and opens a pull request
- Responds to review comments
Source: github.com/features/copilot. GitHub Copilot coding agent is a trademark of GitHub; this guide is not affiliated with or endorsed by them.
What you need on MIOSA
Each row is one thing to create before you start. The number matches the step that uses it.
- Organization and API key Scopes every call; a workspace key is all a worker needs.
miosa api-key create app-key --preset agentDocs - Sandbox The isolated Linux workspace the agent writes code and runs commands in.
miosa create app-box --template nextjs --waitDocs - A workspace per customer Isolates each customer’s machines, deployments, and data as they onboard.
miosa workspace create customer-1Docs - Branding and white-label Your name and slug on previews, deployments, and the desktop; customers never see MIOSA.
miosa orgDocs - Usage metering and bill-to Usage per customer, and which account pays for new machines.
miosa org billDocs - Agent and harness Turns a prompt into work: pick the harness and model a run uses.
miosa agent harnessesDocs
Architecture
How it maps onto MIOSA
A workspace the agent can break safely -> a MIOSA sandbox per task, with the repo cloned into /workspace
The agent edits files and runs commands -> agent runs (`miosa prompt`, client.runs) streaming events on that sandbox (`miosa prompt --sandbox ... --harness ...`)
Parallel tasks -> one sandbox per task or branch, sandbox snapshots and fork to try a second approach
Results you can review -> `miosa run files`, `miosa run outputs`, and the git diff inside the sandbox
Issue in, pull request out -> git clone, branch, commit and push inside the sandbox using a repo-scoped token, then open the PR with your Git host API
Data and storage
Keep a tasks table in your own datastore: task id, repo, branch, sandbox id, run id, status, result links, and the user or customer it belongs to. The code itself lives in the sandbox and in Git, not in your database.
Nothing else needs storage: Git is the system of record for the code.
Auth and tenancy
Your organization is the platform; customers never get a MIOSA account, they sign into YOUR product. One workspace per customer, created as they onboard, isolates their machines, runs and data.
miosa workspace create github-copilot-customer-1Tag every machine and run with the customer id in `metadata`, and never query across customers. Meter usage per customer with GET /api/v1/usage and set who pays with PUT /api/v1/bill-to (/docs/platform/usage-and-billing).
Agent loop
Harness: OSA is MIOSA's own harness and works with any model provider you connect, including your own model.
Model: Anthropic (Claude). Calls use my own provider key (`miosa connections add models`); MIOSA platform keys are never used.
Sessions: one chat per project or conversation, so the agent keeps its context. The first `miosa prompt` on a sandbox uses `--new-chat` (a chat id is printed); every later turn passes `--chat <chat-id>`. `--reuse chat` keeps one new machine per chat so files persist.
Streaming: follow a run with `miosa run follow <run-id>` or client.runs.streamEvents(run.id), and steer or stop it with `miosa run steer` and `miosa run interrupt`.
The harness runs headless INSIDE the task sandbox with the repo checked out. It edits files, runs the project's own commands and commits; you never apply its edits from outside.
Parallel sessions are separate sandboxes (and separate chats). Snapshot before a risky change and fork to try a second approach.
Steps
Create one sandbox per task or branch so parallel tasks never share state.
miosa create github-copilot-task-1 --size medium --waitCheck: The sandbox is running; two tasks have two sandboxes.
Clone the repository and create the task branch. Pass the Git token per exec or through the Secrets API; do not store it in the sandbox `env`.
miosa exec github-copilot-task-1 -- git clone <repo-url> /workspace/repomiosa exec github-copilot-task-1 --cwd /workspace/repo -- git checkout -b task/<task-id>Check: The repo is in /workspace/repo on the task branch.
Dispatch the harness with the task.
miosa prompt --sandbox github-copilot-task-1 --harness osa --model <anthropic-model-id> --chat <chat-id> "Resolve issue <number>; run the tests; commit your work"Check: `miosa run list --status running` shows the run and events start streaming.
Follow the run, and steer or stop it from your UI.
miosa run follow <run-id>miosa run steer --sandbox github-copilot-task-1 "also add tests"miosa run interrupt --sandbox github-copilot-task-1Check: The UI shows live events; a steer lands on the next turn; interrupt stops the agent.
Verify independently of the agent: run the test command yourself.
miosa exec github-copilot-task-1 --cwd /workspace/repo -- npm testCheck: Tests exit 0 in the sandbox, not just in the agent's summary.
Hand back a pull request: push the branch and open the PR with your Git host API, linking the MIOSA run id in the description.
miosa run files <run-id>miosa run download <run-id> <file-id> --output ./resultmiosa exec github-copilot-task-1 --cwd /workspace/repo -- git push origin task/<task-id>Check: The diff is reviewable outside the sandbox and the run id is attached to it.
Close out. For one-shot tasks let MIOSA do it (`miosa prompt --new-machine ... --after-run destroy`); keep or snapshot the sandbox when the user may continue.
Check: No orphaned sandboxes remain after the task is closed.
Limits and costs
Set `--max-time` on every run so a stuck agent cannot run forever; use `--notify-email` or a webhook for long tasks.
Give the agent a token scoped to one repository, and only the permissions the task needs.
Parallel tasks multiply cost: cap concurrency per user or customer.
Prototype: keep it to one machine at the default size, skip replicas and custom hostnames you do not need, and delete everything when you are done.
Acceptance checks
Two tasks run at the same time in two sandboxes without touching each other.
A finished task leaves a reviewable branch or diff and the run id.
Nothing was deployed or published: the deliverable is the diff.
Each customer is isolated in its own workspace and usage is metered against them.
Everything it created can be deleted with nothing left running.