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Enju
Pricing
- Model
- Free
Summary
You swap in a new coding agent, run it against your backlog, and have no idea whether it actually finished the task or just looked like it did — until the PR breaks main. Orbit is a validation harness that wraps any JSON-speaking coding agent and refuses to call a task done until tests, lint, and type checks say otherwise.
Orbit structures agent work into discrete, dependency-ordered loops: one task per run, deterministic validation gates, and four output artifacts that record exactly what the agent returned, how the run scored against a rubric, and what should happen next. The demo runs without an API key, which means you can evaluate the harness itself before spending a single token. Where it gets constrained: Orbit is a harness, not a scheduler — it does not autonomously drive through a backlog or retry failed orbits on its own. Teams wiring it into CI pipelines write the outer loop themselves.
Bottom line: Orbit is the right call when you need auditable, artifact-backed proof that an agent task passed validation before it touches your branch — but if you need the harness to self-drive retries and backlog progression without human-authored glue code, you are writing that orchestration layer yourself.
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Pros
Sign in to edit- Agent-neutral adapter contract, so you can run Claude and Codex against the same task definition and compare structured evaluation artifacts instead of arguing over impressions.
- Validation gates (tests, lint, type checks) block task completion until checks pass, which means agent output that merely looks correct cannot close an orbit and cannot reach your branch.
- Dependency-aware backlog selection keeps each run scoped to a single, well-bounded task, so you avoid the compounding failures that come from an agent chaining through multiple ambiguous steps at once.
- Mock-mode replay demo requires no API key, so you can evaluate Orbit's harness behavior and artifact output without spending tokens or standing up external credentials.
- MIT licensed and self-hostable, which means no vendor dependency on the validation layer for a security-sensitive or air-gapped environment.
Cons
Sign in to edit- Orbit does not drive its own retry or backlog progression loop — when an orbit fails validation, a human or an external script decides what runs next. Teams expecting autonomous multi-task execution will write a significant orchestration layer on top of the harness before it matches that expectation.
- There is no API surface and no native CI integration out of the box. Connecting Orbit to a GitHub Actions pipeline or a merge queue requires an adapter the team authors; the docs describe this as a contribution pattern, not a built-in feature.
- The harness is scoped to coding agents that speak a JSON CLI contract. Teams already invested in a coding agent that does not expose a structured CLI output format will hit an integration wall immediately and either write a translation shim or move to a validation approach their agent already supports natively.
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About
- Platforms
- Platform-agnostic (Python); local or remote execution
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-06-01T10:23:44.333Z
Best For
Who it's for
- Teams evaluating and comparing different AI coding agents
- Developers building custom agent orchestration and validation logic
- Validating agent output with deterministic gates before merge
- Local/deterministic testing of multi-agent workflows
What it does well
- Testing and iterating on AI agent validation workflows without buying API tokens
- Comparing different coding agents against identical task definitions and evaluation criteria
- Running self-healing repository workflows that verify test passes before marking tasks complete
- Executing ordered backlogs of agent tasks with dependency awareness and structured evaluation
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Frequently Asked Questions
- Is Enju free?
- Yes — Enju is fully free to use. There is no paid tier.
- Is Enju open source?
- Yes. Enju is open source.
- Can I self-host Enju?
- Yes. Enju supports self-hosting on your own infrastructure.
- What platforms does Enju support?
- Enju is available on: Platform-agnostic (Python); local or remote execution.
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Curated lists that include this category
Coding agents produce output that looks correct until it isn’t — and without a structured checkpoint, the failure surfaces at review, not at generation. Orbit addresses this by wrapping any JSON-speaking coding agent (Claude, Codex, Cursor, or a custom CLI) in a validation loop: it selects a task from a dependency-ordered backlog, runs the agent, executes tests and lint as gates, and records the outcome in four structured artifacts before the orbit is allowed to close. Nothing advances unless the checks pass.
The artifact trail is Orbit’s sharpest differentiating feature. Every run produces an agent-result.json (structured status, changed files, raw output), an evaluation.json (rubric scoring across task focus, completion, diff signal, and validation), a review.json (accept, iterate, or stop recommendation), and a progress.md (human-readable mission log). When you are comparing two coding agents against the same task definition, you are comparing structured JSON artifacts — not reading through commit diffs and forming opinions.
Orbit fits teams who are evaluating which coding agent to standardize on, or who want deterministic gates before agent-generated code reaches a merge queue. The ‘self-healing repo’ pattern described in the docs — feed Orbit failing tests and require proof of a passing run before closing the task — is a concrete use case that works without API cost, since the replay demo runs in mock mode locally. Where Orbit does not fit: it has no scheduler, no retry loop, and no autonomous backlog driver. The harness advances one orbit at a time; the outer orchestration is yours to build.
Orbit is MIT licensed, self-hostable, and intentionally scoped small. The vendor page describes it as ‘intentionally small,’ and the contribution guidance reflects that — adapters, demo missions, and mission templates are the extension surface, not a plugin ecosystem. Teams who need to connect it to an existing CI system write an adapter; the repo structure and starter issues support that path.
