by zqiren
The Project Agent: Where every agent's work compounds in your local project
# Add to your Claude Code skills
git clone https://github.com/zqiren/OrbitalLast scanned: 7/14/2026
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}Orbital is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by zqiren. The Project Agent: Where every agent's work compounds in your local project. It has 140 GitHub stars.
Yes. Orbital passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/zqiren/Orbital" and add it to your Claude Code skills directory (see the Installation section above).
Orbital is primarily written in Python. It is open-source under zqiren on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Orbital against similar tools.
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Orbital works like Claude Code or Codex: ask it to research, plan, write, run commands, browse the web, or operate your tools.
The difference is that Orbital treats a local folder as a long-running project. It maintains the project's context on its own — where it left off, what's next, and how to do it — as files inside that folder. Every new task starts from everything learned before it, so work compounds instead of resetting to zero.
Orbital can also dispatch Claude Code, Codex, Gemini CLI, Cursor, and other CLI agents. Every dispatch briefs the worker on the project and the task and points it at the relevant files — you never re-explain the project. Orbital watches the run, reads the result against the project's context, and writes the outcome back in. The more you delegate, the more it knows.
People already use several capable agents at work — for the newest model, the leftover quota, or because a particular tool is better at the job.
But each agent works inside its own session, with its own context and history. When you move between sessions or tools, you become responsible for carrying the project between them: restating goals, explaining previous decisions, locating artifacts, and checking what was left unfinished. You end up working as their intern, ferrying context between them to keep your own project moving.
Orbital changes the unit of work from the session to the project.
A project agent stays responsible for the project across tasks, sessions, and worker agents. It maintains the shared context, decides what needs to happen next, delegates when useful, and records every outcome back into the project.
Individual agents complete tasks. Orbital keeps the project moving.
Orbital maintains five things that normally disappear or fragment between agent sessions — all of them as plain files in your project folder:
PROJECT_STATE.md)DECISIONS.md)LESSONS.md)queue.json). Every queued task ends Completed or Blocked — an agent that stops without a verdict gets re-prompted, then force-blocked with a reason. Nothing drifts away silently.orbital/output/)These stay in the local project and become context for future work. On a cold start, Orbital assembles them into its own system prompt before it acts.
When Orbital delegates, the worker is pointed at those same files and told they are authoritative — that briefing is rendered fresh on every dispatch, not something you paste in. Each worker also keeps its own memory file inside the project, so it accumulates its own experience across dispatches. When the task finishes, Orbital reads the result and records what matters back into the project.
The worker can change. The project continues.
Set up once — pick an LLM provider and paste your API key; optionally connect accounts your agents will need.
Create a project — name it, choose the local folder that holds your work, set an autonomy level.
Give Orbital a task — ask it to research, plan, write, code, browse, or work with files.
Orbital maintains the context — it keeps the project's state, decisions, lessons, queue, and artifacts current as the work progresses.
Orbital delegates when useful — it dispatches work to Claude Code, Codex, Gemini CLI, Cursor, or another CLI agent against the same accumulated context.
Every result becomes part of the project — future tasks begin on top of the work that came before them.
flowchart LR
You["You"] --> Orbital["Orbital<br/>Project agent"]
Orbital <--> Project["Local project folder<br/>State · Decisions · Lessons · Queue · Artifacts"]
Orbital -->|briefs + dispatches| Workers["Worker agents<br/>Claude Code · Codex · Gemini CLI · Cursor"]
Workers -->|results| Orbital
Orbital -->|every task ends<br/>Completed or Blocked| Project
Phone["Your phone"] -.->|approvals · check-ins| Orbital
Suppose you ask Orbital to research a competitor.
Orbital gathers the initial information and records the findings inside the project. It then dispatches the token-heavy technical investigation to Claude Code, which starts by reading the project's goals, constraints, and previous decisions from the project folder.
When Claude Code finishes, Orbital reads its findings and records the useful results back into the project.
A week later, you ask Orbital to draft a launch plan. It begins with that earlier research, the decisions made since, and the artifacts already produced.
You do not begin again with an empty chat. You continue the project.
Launch Orbital — the setup wizard guides you through two steps:
Step 1 — LLM Provider: Pick a provider from the preset cards, follow the key-console link to grab an API key, and paste it in. Supports DeepSeek, Anthropic, OpenAI, Moonshot, and a dozen other providers.
Step 2 — Connect Your Accounts: Link API connectors (Google Calendar, Drive) and sign in to sites your agents will need (Google, GitHub, etc.) so they can browse without getting blocked by CAPTCHAs. Everything here is optional and can be done later in Settings.
Create a project — give it a name, pick a workspace directory, set an autonomy level
Why the project never loses its memory
Why you can swap agents mid-project
Why you can delegate without watching