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Sculptor

#139 agent harnessverified Sep 4, 2026sculptor-v0.48.0

Imbue's desktop app for running coding agents in parallel, each in an isolated workspace with live diff review and PR creation

Key differences

Imbue's desktop app for running coding agents in parallel, each in an isolated workspace with live diff review and PR creation

  • Runs local. Free and open source under MIT; requires your own Claude CLI login by subscription or API key. No pricing page is published
  • Runs multiple agents. Listed for 165 of 194 tools in this category.
  • Keep in mind: The marketing page says every agent runs in its own container, but the help docs state the default workspace is a git worktree and describe a Docker container backend as experimental.

“It ships a feature called CI Babysitter, which is the most accurate name anyone in this category has managed.”

Website Docs 234 starsCompare vs…Dispute a fact
Appeal a claim or request ownership transfer

What it is

Sculptor is a desktop application from Imbue that runs coding agents in parallel, each in its own workspace, by default a git worktree on its own branch so your working tree is untouched. It integrates closely with Claude Code, running it as a streaming-JSON process with the control protocol enabled and substituting its own ask-user and plan tools, and also supports the Pi harness and other terminal agents. It ships a built-in terminal, live diff review, GitHub pull request creation and a CI Babysitter that dispatches an agent to fix failing checks. Imbue labels it an experimental research preview.

Specification

Source verification

Row snapshot checked 2026-09-04. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

install
Needs individual review
license
Needs individual review
capabilities
Needs individual review
models
Needs individual review
pricing
Needs individual review
status
Needs individual review

Architecture

Type
Agent harness
Runssrc ↗
local
Platforms
macos, linux
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
Claude
Bring your own model
Yes
Local models
No

Protocols

MCP clientunsourced
No
MCP server
No
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
Yes
Browser control
No
Sandboxed execution
No
The marketing page says every agent runs in its own container, but the help docs state the default workspace is a git worktree and describe a Docker container backend as experimental.
Multi-agent
Yes
Headless / CI
No

Cost

Modelsrc ↗
byok
Starts at
n/a
Free tier
Yes
Bring your own key
Yes

Free and open source under MIT; requires your own Claude CLI login by subscription or API key. No pricing page is published

Openness

Open sourcesrc ↗
Yes
License
MIT
First release
2025-08
previewworktreesparallel-agentsmulti-agentclaude-codeopen-source

Los Agentes on Sculptor

Who are they?
The ruling
El JuezThe judge

El Crítico found the marketing page and the help docs describing different isolation; El Profesor found the integration underneath it to be genuinely careful work.

Trial only
Reasoning and trade-offs · AI analysis

El Crítico's finding is a discrepancy: the product page says each agent gets its own container while the help docs record a git worktree as the default and the container backend as experimental. El Profesor looks one layer down and finds a disciplined integration with the agent it drives, using a real control protocol.

El Profesor is right about the engineering and El Crítico about the claim; the engineering does not rescue the claim, and he is overruled only where he treats a research preview as a product. La Inversora settles the rest. Trial only: assume worktree isolation, not containers, and keep it off anything you cannot lose.

Agree with El Juez?
El AmigoThe friend

Pick it if you want three agents attempting a task on three branches and a pull request at the end; pick Claude Squad if you would rather that happened in a terminal.

6.3
Reasoning and trade-offs · AI analysis

You will get the most out of this when a task has more than one reasonable approach. The trait that decides it in daily use is that each agent gets its own branch and its own workspace, so running three attempts is normal rather than reckless, and the thing you review at the end is a pull request on GitHub rather than a pile of edits in your checkout.

Pick it if comparing attempts is how you like to work. Pick Claude Squad for the same idea in a terminal, or a single-agent tool if you would rather spend your attention on one attempt done well.

reliability
5
usefulness
7
cost
8
longevity
5
Agree with El Amigo?
El CríticoThe critic

The product page says every agent runs in its own container; the help documentation says the default workspace is a git worktree and the container backend is experimental.

5.3
Reasoning and trade-offs · AI analysis

Two documents from the same vendor disagree about the safety model, and the more optimistic one is the page a buyer reads first. A worktree separates files and shares everything else, including the shell, the network and your credentials, so a user who believed the marketing has a materially different threat model from the one they actually have. The vendor labels the whole thing an experimental research preview, which is honest and does not resolve the contradiction.

What it does right: changes are reviewed live as diffs before they go anywhere, so the human checkpoint is built into the loop rather than offered as an option.

reliability
4
usefulness
6
cost
7
longevity
4
Agree with El Crítico?
El ProfesorThe professor

It drives the wrapped agent as a streaming-JSON process with the control protocol enabled and substitutes its own ask-user and plan tools, which is interception done properly.

6.5
Reasoning and trade-offs · AI analysis

The integration deserves attention. 1. The underlying agent is run as a structured process over a documented control channel rather than by parsing its display, so the wrapper reads events instead of pixels. 2. Two tools in the agent's namespace are replaced with the host's own implementations, which lets the surrounding application own the moments where a human is asked a question or a plan is formed.

That second choice is the substantive one: it means the supervision layer is inside the agent's tool loop rather than bolted around it. No evaluation is published, and the vendor's own preview labelling is the correct signal about maturity.

reliability
7
usefulness
6
cost
7
longevity
6
Agree with El Profesor?
La InversoraThe investor

This is a research lab's artefact rather than a company's product: no pricing page, a preview label, and a couple of hundred stars after a year.

5.3
Reasoning and trade-offs · AI analysis

Read the distribution before the features. Roughly two hundred stars in a category where competitors count them in thousands says this has not found an audience, and there is no pricing page at all, which means nobody has been asked to pay and therefore nobody has validated that they would. A research organisation publishing tooling is a legitimate activity and not a business.

The exit here is a paper or a pivot, not an acquisition; the interesting asset is the supervision technique rather than the application. Position: adopt as a source of ideas, and do not put a team's workflow behind a lab's side output.

reliability
5
usefulness
6
cost
6
longevity
4
Agree with La Inversora?
La JefaThe CTO

It creates pull requests and dispatches an agent at failing checks, and I cannot tell an auditor who authorised any of it, on a platform list that excludes Windows.

4.8
Reasoning and trade-offs · AI analysis

A tool that opens pull requests and then sends an agent to fix failing checks is a tool acting on my repositories, and the row gives me no single sign-on, no SCIM and no audit trail to attach those actions to a person. That is the whole conversation. Distribution narrows it further: Apple Silicon and Linux only, so a third of my engineers cannot install it, and each user needs their own subscription with the upstream vendor.

Onboarding is short, which is not the problem. Not yet. Bring me identity and a Windows build, in that order.

reliability
4
usefulness
5
cost
6
longevity
4
Agree with La Jefa?
El HackerThe tinkerer

MIT, which is the best thing about it, and after that I get no MCP in either direction and no model that is not the one vendor's.

5.8
Reasoning and trade-offs · AI analysis

MIT is a real gift on a desktop application, because it means the supervision code is readable and a fork is legitimate, and the repository is public rather than a marketing mirror. That is where my enthusiasm stops. There is no MCP support in either direction, so the servers I run are simply not part of this, and the agent underneath is one vendor's client authenticated with my own login.

Nothing runs on my hardware. I would clone this to study how it takes over an agent's tool loop, and I would not make it my daily driver.

reliability
6
usefulness
5
cost
7
longevity
5
Agree with El Hacker?