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Tab Council
Pricing
- Model
- Free
Summary
AI coding agents lie convincingly — they claim completion, the diff looks plausible, and the tests were never actually run. Orbit exists for the moment after that trust breaks.
Orbit wraps agent coding work in a bounded loop: it selects a dependency-ordered task, hands it to whichever agent you've wired up, then requires passing tests, lint, and type checks before the task closes. Every run produces structured JSON — what the agent returned, how it scored against a rubric, and a human-readable progress log. Nothing advances on the agent's word alone. The ceiling appears when your workflow needs anything beyond single-task validation loops: multi-repo coordination, branching logic between tasks, or a hosted dashboard for non-engineering stakeholders all require you to build on top of Orbit yourself.
Bottom line: Orbit is the right harness for a self-healing repo where failing tests drive agent work and proof-of-fix is non-negotiable — but if you need a managed platform, a UI your PM can check, or multi-agent parallelism out of the box, you are writing that infrastructure yourself.
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Pros
Sign in to edit- Validation gates run real tests, lint, and type checks before a task closes, so an agent cannot mark work complete without machine-verifiable proof — which eliminates the entire category of 'it worked on my machine' agent claims.
- Agent-neutral adapter contract means swapping the underlying coding model is a configuration change, not a rewrite, so you can compare two agents on identical tasks using the same artifact rubric instead of gut feel.
- Dependency-ordered backlog execution advances one verified task at a time, so large refactoring or migration projects do not accumulate unvalidated state across dozens of agent runs.
- Every run writes structured JSON artifacts — result, evaluation, review recommendation, and a human-readable progress log — so audits, rollbacks, and post-mortems have a durable evidence trail rather than reconstructed memory.
- MIT licensed and self-hosted with a four-command local install, so there is no vendor dependency, no data leaving your environment, and no paid tier gating any part of the validation loop.
Cons
Sign in to edit- Orbit enforces validation through your existing test suite and lint rules — codebases with sparse coverage get toothless gates, and the harness has no mechanism to generate or scaffold the tests it needs; teams in that position must build coverage before Orbit adds value.
- There is no hosted runner, web dashboard, or notification layer; non-engineering stakeholders cannot monitor progress without someone piping the JSON artifacts into a separate reporting tool — at which point you are maintaining Orbit plus that layer.
- The harness handles one task per orbit sequentially; workflows that need agents running in parallel on independent branches, or that need branching logic based on what a previous step returned, require you to build a coordination layer on top — teams whose primary need is multi-agent parallelism will reach for a different tool before the first sprint ends.
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About
- Platforms
- Linux, macOS, Windows (Python 3.7+)
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- 2026-06-02T09:09:28.330Z
Best For
Who it's for
- Teams deploying AI coding agents in production codebases
- Developers building agent adapters and experimenting with model swaps
- Validation-critical workflows where proof matters more than agent claims
- Codebases with comprehensive test coverage and lint rules
- AI-driven code migration and large-scale refactoring projects
What it does well
- Validating AI agent coding work with real test and lint checks before merge
- Running dependency-ordered task queues across a codebase with agent execution
- Comparing multiple coding agents on the same task using deterministic replay
- Self-healing repositories: feeding agents failing tests and requiring proof of fix
- Building repeatable, auditable agent workflows for code migration and refactoring
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Frequently Asked Questions
- Is Tab Council free?
- Yes — Tab Council is fully free to use. There is no paid tier.
- Is Tab Council open source?
- Yes. Tab Council is open source.
- Does Tab Council have an API?
- Yes. Tab Council exposes a developer API. See the official documentation at https://github.com/vaddisrinivas/tab-council for details.
- Can I self-host Tab Council?
- Yes. Tab Council supports self-hosting on your own infrastructure.
- What platforms does Tab Council support?
- Tab Council is available on: Linux, macOS, Windows (Python 3.7+).
Hours Saved & ROI Stories Community
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Curated lists that include this category
Every AI coding agent will tell you it fixed the bug. Orbit makes it prove it. The tool runs as a local harness — you clone it, point it at a backlog of dependency-ordered tasks, and it advances one ‘orbit’ at a time: select task, invoke agent adapter, run real validation gates (tests, lint, type checks), and write durable artifacts before the loop can close. The vendor describes the full artifact set as agent-result.json, evaluation.json, review.json, and progress.md — a structured evidence trail covering what changed, how the run scored on a rubric, and whether the reviewer should accept, iterate, or stop.
The differentiating design choice is agent-neutrality enforced by a contract, not by integration complexity. Claude, Codex, Cursor, or any JSON-speaking CLI plugs in behind the same adapter interface. This means you can run the same task against two agents, compare their artifacts side by side, and make the swap decision on evidence rather than impressions — the vendor calls this ‘adapter experiments.’ The deterministic replay demo runs without an API key, which makes onboarding and CI testing of the harness itself tractable from the first hour.
Orbit fits tightly into codebases that already have test coverage and lint rules, because those are the gates the harness enforces. Without them, validation is toothless and the loop closes on nothing. It fits teams doing large-scale migration or refactoring work — the kind of backlog that needs to advance one verified step at a time without a human approving each commit manually. Where it breaks: Orbit is intentionally small by the vendor’s own description. There is no hosted runner, no web UI, no built-in parallelism across tasks, and no orchestration layer for workflows that branch based on what a previous agent returned. Teams hitting those limits are adding their own tooling around the harness.
Setup requires Git, Python, and a virtual environment — the vendor documents this as a four-command install. The MIT license means you can fork, embed, or extend the harness without restriction. Contributions the project explicitly calls for are adapters for additional coding agents, replay demos, and mission templates — so the surface area for extending it is narrow and intentional.