openai-symphony-autonomous-agents

aradotso/trending-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/aradotso/trending-skills --skill openai-symphony-autonomous-agents
0 commentsdiscussion
summary

Skill by ara.so — Daily 2026 Skills collection.

skill.md

OpenAI Symphony

Skill by 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

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

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

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

cd elixir
mix deps.get

Configuration (elixir/config/config.exs)

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

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

# 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)

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

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

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.
how to use openai-symphony-autonomous-agents

How to use openai-symphony-autonomous-agents on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add openai-symphony-autonomous-agents
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aradotso/trending-skills --skill openai-symphony-autonomous-agents

The skills CLI fetches openai-symphony-autonomous-agents from GitHub repository aradotso/trending-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/openai-symphony-autonomous-agents

Reload or restart Cursor to activate openai-symphony-autonomous-agents. Access the skill through slash commands (e.g., /openai-symphony-autonomous-agents) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.547 reviews
  • Sakura Reddy· Dec 28, 2024

    Keeps context tight: openai-symphony-autonomous-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Dec 20, 2024

    openai-symphony-autonomous-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Arjun Verma· Dec 20, 2024

    I recommend openai-symphony-autonomous-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Anaya Gupta· Dec 4, 2024

    Registry listing for openai-symphony-autonomous-agents matched our evaluation — installs cleanly and behaves as described in the markdown.

  • William Bansal· Nov 23, 2024

    openai-symphony-autonomous-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakura Jain· Nov 19, 2024

    openai-symphony-autonomous-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sakshi Patil· Nov 11, 2024

    Keeps context tight: openai-symphony-autonomous-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aarav Smith· Nov 11, 2024

    Useful defaults in openai-symphony-autonomous-agents — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sophia Abebe· Oct 14, 2024

    openai-symphony-autonomous-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aarav Thomas· Oct 10, 2024

    openai-symphony-autonomous-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

showing 1-10 of 47

1 / 5