skaro.dev

What It Is

Skaro is a local spec-driven workspace for AI software development. It is not just a code completion tool; instead, it adds a layer of engineered artifact management on top of an existing code repository. Constitution, architecture, ADRs, DevPlans, and tasks are all stored in the repo, while a local web dashboard shows project status, the current phase, progress, and next steps.

Core Capabilities

Functionally, Skaro emphasizes the idea that “critical context should not be left inside chat.” Architecture can be viewed, edited, and approved as a standalone artifact; ADRs use status and history to lock down key decisions; DevPlans record milestones, priorities, and execution order; and tasks move through stages such as Clarify, Plan, Implement, and Tests. It also integrates Git status, diff, stage, commit, push, branch switching, and automatic commits after task completion, making it suitable for reviewing and committing AI-generated code immediately. On the AI side, Skaro supports assigning different models to architect, coder, and reviewer roles, separating architecture planning, implementation, and quality checks.

Tech Stack, Deployment, and Ecosystem

The site shows that Skaro can be installed via an install script, pipx, or uv. With just two commands, you can run skaro init to initialize .skaro/ and then use skaro ui to launch the local dashboard. It supports a verify command that can run on the host, inside a Docker Compose service, or with a command prefix. In terms of framework support, the main content only explicitly mentions constitution presets for React, Vue.js, Angular, and similar frameworks, while broadly claiming coverage for frontend, backend, and mobile; no detailed language matrix is provided. Ecosystem entry points include GitHub, Docs, PyPI, Telegram, and Discord.

Pricing and Limitations

The main content does not provide commercial pricing; it only shows a Donate link. Since the project appears to be available via GitHub/PyPI, its value for money is likely strong, but the license, model providers, API configuration, enterprise support, and documentation depth are not clearly explained in the main text. Another potential barrier is that teams need to buy into a spec-driven workflow; otherwise, maintaining artifacts such as the constitution, ADRs, and DevPlans may feel somewhat heavy.

Who It’s For and Access from China

Skaro is well suited to individual developers and small teams that already rely heavily on AI coding but struggle with lost context, untraceable architecture decisions, and AI-generated changes that are difficult to review. The main content does not state how accessible it is from China. External dependencies such as GitHub, PyPI, model APIs, Telegram, and Discord may introduce uncertainty. Alternatives worth watching include Cursor, Continue, Aider, Claude Code, OpenHands, and others.