openai-symphony-autonomous-agents
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents.
Best use case
openai-symphony-autonomous-agents is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents.
Teams using openai-symphony-autonomous-agents should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/openai-symphony-autonomous-agents/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How openai-symphony-autonomous-agents Compares
| Feature / Agent | openai-symphony-autonomous-agents | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# OpenAI Symphony
> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to **manage work** instead of **supervising coding agents**. Instead of watching an agent code, you define tasks (e.g. in Linear), and Symphony spawns agents that complete them, provide proof of work (CI status, PR reviews, walkthrough videos), and land PRs autonomously.
---
## What Symphony Does
- Monitors a work tracker (e.g. Linear) for tasks
- Spawns isolated agent runs per task (using Codex or similar)
- Each agent implements the task, opens a PR, and provides proof of work
- Engineers review outcomes, not agent sessions
- Works best in codebases using [harness engineering](https://openai.com/index/harness-engineering/)
---
## Installation Options
### Option 1: Ask an agent to build it
Paste this prompt into Claude Code, Cursor, or Codex:
```
Implement Symphony according to the following spec:
https://github.com/openai/symphony/blob/main/SPEC.md
```
### Option 2: Use the Elixir reference implementation
```bash
git clone https://github.com/openai/symphony.git
cd symphony/elixir
```
Follow `elixir/README.md`, or ask an agent:
```
Set up Symphony for my repository based on
https://github.com/openai/symphony/blob/main/elixir/README.md
```
---
## Elixir Reference Implementation Setup
### Requirements
- Elixir + Mix installed
- An OpenAI API key (for Codex agent)
- A Linear API key (if using Linear integration)
- A GitHub token (for PR operations)
### Environment Variables
```bash
export OPENAI_API_KEY="sk-..." # OpenAI API key for Codex
export LINEAR_API_KEY="lin_api_..." # Linear integration
export GITHUB_TOKEN="ghp_..." # GitHub PR operations
export SYMPHONY_REPO_PATH="/path/to/repo" # Target repository
```
### Install Dependencies
```bash
cd elixir
mix deps.get
```
### Configuration (`elixir/config/config.exs`)
```elixir
import Config
config :symphony,
openai_api_key: System.get_env("OPENAI_API_KEY"),
linear_api_key: System.get_env("LINEAR_API_KEY"),
github_token: System.get_env("GITHUB_TOKEN"),
repo_path: System.get_env("SYMPHONY_REPO_PATH", "./"),
poll_interval_ms: 30_000,
max_concurrent_agents: 3
```
### Run Symphony
```bash
mix symphony.start
# or in IEx for development
iex -S mix
```
---
## Core Concepts
### Isolated Implementation Runs
Each task gets its own isolated run:
- Fresh git branch per task
- Agent operates only within that branch
- No shared state between runs
- Proof of work collected before PR merge
### Proof of Work
Before a PR is accepted, Symphony collects:
- CI/CD pipeline status
- PR review feedback
- Complexity analysis
- (optionally) walkthrough videos
---
## Key Elixir Modules & Patterns
### Starting the Symphony supervisor
```elixir
# In your application.ex or directly
defmodule MyApp.Application do
use Application
def start(_type, _args) do
children = [
Symphony.Supervisor
]
Supervisor.start_link(children, strategy: :one_for_one)
end
end
```
### Defining a Task (Symphony Task struct)
```elixir
defmodule Symphony.Task do
@type t :: %__MODULE__{
id: String.t(),
title: String.t(),
description: String.t(),
source: :linear | :manual,
status: :pending | :running | :completed | :failed,
branch: String.t() | nil,
pr_url: String.t() | nil,
proof_of_work: map() | nil
}
defstruct [:id, :title, :description, :source,
status: :pending, branch: nil,
pr_url: nil, proof_of_work: nil]
end
```
### Spawning an Agent Run
```elixir
defmodule Symphony.AgentRunner do
@doc """
Spawns an isolated agent run for a given task.
Each run gets its own branch and Codex session.
"""
def run(task) do
branch = "symphony/#{task.id}-#{slugify(task.title)}"
with :ok <- Git.create_branch(branch),
{:ok, result} <- Codex.implement(task, branch),
{:ok, pr_url} <- GitHub.open_pr(branch, task),
{:ok, proof} <- ProofOfWork.collect(pr_url) do
{:ok, %{task | status: :completed, pr_url: pr_url, proof_of_work: proof}}
else
{:error, reason} -> {:error, reason}
end
end
defp slugify(title) do
title
|> String.downcase()
|> String.replace(~r/[^a-z0-9]+/, "-")
|> String.trim("-")
end
end
```
### Linear Integration — Polling for Tasks
```elixir
defmodule Symphony.Linear.Poller do
use GenServer
@poll_interval Application.compile_env(:symphony, :poll_interval_ms, 30_000)
def start_link(opts \\ []) do
GenServer.start_link(__MODULE__, opts, name: __MODULE__)
end
def init(_opts) do
schedule_poll()
{:ok, %{processed_ids: MapSet.new()}}
end
def handle_info(:poll, state) do
case Symphony.Linear.Client.fetch_todo_tasks() do
{:ok, tasks} ->
new_tasks = Enum.reject(tasks, &MapSet.member?(state.processed_ids, &1.id))
Enum.each(new_tasks, &Symphony.AgentRunner.run/1)
new_ids = Enum.reduce(new_tasks, state.processed_ids, &MapSet.put(&2, &1.id))
schedule_poll()
{:noreply, %{state | processed_ids: new_ids}}
{:error, reason} ->
Logger.error("Linear poll failed: #{inspect(reason)}")
schedule_poll()
{:noreply, state}
end
end
defp schedule_poll do
Process.send_after(self(), :poll, @poll_interval)
end
end
```
### Linear API Client
```elixir
defmodule Symphony.Linear.Client do
@linear_api "https://api.linear.app/graphql"
def fetch_todo_tasks do
query = """
query {
issues(filter: { state: { name: { eq: "Todo" } } }) {
nodes {
id
title
description
}
}
}
"""
case HTTPoison.post(@linear_api, Jason.encode!(%{query: query}), headers()) do
{:ok, %{status_code: 200, body: body}} ->
tasks =
body
|> Jason.decode!()
|> get_in(["data", "issues", "nodes"])
|> Enum.map(&to_task/1)
{:ok, tasks}
{:error, reason} ->
{:error, reason}
end
end
defp headers do
[
{"Authorization", System.get_env("LINEAR_API_KEY")},
{"Content-Type", "application/json"}
]
end
defp to_task(%{"id" => id, "title" => title, "description" => desc}) do
%Symphony.Task{id: id, title: title, description: desc, source: :linear}
end
end
```
### Proof of Work Collection
```elixir
defmodule Symphony.ProofOfWork do
@doc """
Collects proof of work for a PR before it can be merged.
Returns a map with CI status, review feedback, and complexity.
"""
def collect(pr_url) do
with {:ok, ci_status} <- wait_for_ci(pr_url),
{:ok, reviews} <- fetch_reviews(pr_url),
{:ok, complexity} <- analyze_complexity(pr_url) do
{:ok, %{
ci_status: ci_status,
reviews: reviews,
complexity: complexity,
collected_at: DateTime.utc_now()
}}
end
end
defp wait_for_ci(pr_url, retries \\ 30) do
case GitHub.get_pr_ci_status(pr_url) do
{:ok, :success} -> {:ok, :success}
{:ok, :pending} when retries > 0 ->
Process.sleep(60_000)
wait_for_ci(pr_url, retries - 1)
{:ok, status} -> {:ok, status}
{:error, reason} -> {:error, reason}
end
end
defp fetch_reviews(pr_url), do: GitHub.get_pr_reviews(pr_url)
defp analyze_complexity(pr_url), do: GitHub.get_pr_diff_complexity(pr_url)
end
```
---
## Implementing the SPEC.md (Custom Implementation)
When building Symphony in another language, the spec defines:
1. **Task Source** — poll Linear/GitHub/Jira for tasks in a specific state
2. **Agent Invocation** — call Codex (or another agent) with task context
3. **Isolation** — each run on a fresh branch, containerized if possible
4. **Proof of Work** — CI, review, and analysis before merge
5. **Landing** — auto-merge or present to engineer for approval
Minimal implementation loop in pseudocode:
```elixir
# Core symphony loop
def symphony_loop(state) do
tasks = fetch_new_tasks(state.source)
tasks
|> Enum.filter(&(&1.status == :todo))
|> Enum.each(fn task ->
Task.async(fn ->
branch = create_isolated_branch(task)
invoke_agent(task, branch) # Codex / Claude / etc.
proof = collect_proof_of_work(branch)
present_for_review(task, proof)
end)
end)
Process.sleep(state.poll_interval)
symphony_loop(state)
end
```
---
## Common Patterns
### Limiting Concurrent Agent Runs
```elixir
defmodule Symphony.AgentPool do
use GenServer
@max_concurrent 3
def start_link(_), do: GenServer.start_link(__MODULE__, %{running: 0, queue: []}, name: __MODULE__)
def submit(task) do
GenServer.cast(__MODULE__, {:submit, task})
end
def handle_cast({:submit, task}, %{running: n} = state) when n < @max_concurrent do
spawn_agent(task)
{:noreply, %{state | running: n + 1}}
end
def handle_cast({:submit, task}, %{queue: q} = state) do
{:noreply, %{state | queue: q ++ [task]}}
end
def handle_info({:agent_done, _result}, %{running: n, queue: [next | rest]} = state) do
spawn_agent(next)
{:noreply, %{state | running: n, queue: rest}}
end
def handle_info({:agent_done, _result}, %{running: n} = state) do
{:noreply, %{state | running: n - 1}}
end
defp spawn_agent(task) do
parent = self()
spawn(fn ->
result = Symphony.AgentRunner.run(task)
send(parent, {:agent_done, result})
end)
end
end
```
### Manual Task Injection (No Linear)
```elixir
# In IEx or a Mix task
Symphony.AgentPool.submit(%Symphony.Task{
id: "manual-001",
title: "Add rate limiting to API",
description: "Implement token bucket rate limiting on /api/v1 endpoints",
source: :manual
})
```
---
## Troubleshooting
| Problem | Likely Cause | Fix |
|---|---|---|
| Agents not spawning | Missing `OPENAI_API_KEY` | Check env var is exported |
| Linear tasks not detected | Wrong Linear state filter | Update query filter to match your board's state name |
| PRs not opening | Missing `GITHUB_TOKEN` or wrong repo | Verify token has `repo` scope |
| CI never completes | Timeout too short | Increase `retries` in `wait_for_ci/2` |
| Too many concurrent runs | Default pool size | Set `max_concurrent_agents` in config |
| Branch conflicts | Agent reusing branch names | Ensure task IDs are unique per run |
### Debug Mode
```elixir
# In config/dev.exs
config :symphony, log_level: :debug
# Or at runtime
Logger.put_module_level(Symphony.AgentRunner, :debug)
Logger.put_module_level(Symphony.Linear.Poller, :debug)
```
---
## Resources
- [SPEC.md](https://github.com/openai/symphony/blob/main/SPEC.md) — Full Symphony specification
- [elixir/README.md](https://github.com/openai/symphony/blob/main/elixir/README.md) — Elixir setup guide
- [Harness Engineering](https://openai.com/index/harness-engineering/) — Prerequisite methodology
- [Apache 2.0 License](https://github.com/openai/symphony/blob/main/LICENSE)Related Skills
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