Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for ops, RPA, and back-office automation teams that need to automate workflows on legacy web apps (no APIs, no selectors, just a browser) where traditional RPA (UiPath, Automation Anywhere) is too brittle and too expensive.
Who should use it
Who should skip it
Skip Skyvern-AI/skyvern if the source link, documentation, or setup requirements do not align with your current workflow or stack.
About this signal
Skyvern-AI/skyvern is tracked by RepoRadar as a developer tool in the Radar section. It was first seen on 2026-06-17 and last updated on 2026-06-17. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. Across RepoRadar's eight signals, Skyvern-AI/skyvern is strongest on workflow potential (9.4) and practical usefulness (9.0) and weakest on setup ease (6.4) — a profile worth weighing against your own priorities. This page summarizes the public evidence on the linked source page and states where additional review is still needed. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned Skyvern-AI/skyvern a composite score of 8.3 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 88.0 and never affects the composite score or tier. The risk label of 'conditional' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to evaluate an AI tool before you adopt it for the checklist behind this score.
Risk explanation
AGPL-3.0 license: any modifications to a self-hosted instance that are exposed over a network must be open-sourced — acceptable for internal use, restrictive if you plan to resell as a SaaS; Headless browser automation consumes significant compute and depends on LLM API costs per run — benchmark on real workflows before scaling; Captcha / MFA flows require human-in-the-loop — factor in human review time for high-volume automation.