Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for people who want a real desktop agent that can touch files and browser tasks on their own machine, while keeping the model path flexible enough to swap between local inference and external APIs.
Who should use it
Who should skip it
Move on from accomplish-ai/coworker if the licensing terms, language support, or platform requirements do not fit your project.
About this signal
accomplish-ai/coworker is tracked by RepoRadar as an AI project in the Desktop Agents section. First seen 2026-07-01; the source record was last checked on 2026-07-01. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. accomplish-ai/coworker leads on workflow potential (10.0) and practical usefulness (9.0); its lowest signal is setup ease (6.4), so factor that in before investing setup time. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The accomplish-ai/coworker record combines a 8.7/10 composite score with separate popularity (1.0), risk (conditional), and setup (moderate) signals. See the scoring methodology for the current weights and evidence definitions.
Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
It can manipulate local files and browser tasks, so the first evaluation should stay inside scoped folders and low-risk sites; Using external model APIs or connected productivity tools can expose document content and prompts outside the local machine unless you stay on local models and tightly scoped integrations.