Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for developers who want one practical control surface for installing agent skills, syncing them into tools like Cursor or Codex, and keeping local knowledge plus chat workflows together instead of stitching that stack by hand.
Who should use it
Who should skip it
Move on from Advai-X/advai-cli if the licensing terms, language support, or platform requirements do not fit your project.
About this signal
Advai-X/advai-cli is tracked by RepoRadar as a developer cli in the MCP / Tooling section. It was first seen on 2026-07-01 and last updated on 2026-07-01. The current verdict is 'try now' with a Silver tier and moderate setup difficulty. The standout signals for Advai-X/advai-cli are workflow potential (9.4) and open-source/build quality (8.4), while maturity (5.8) trails — that balance shapes where it fits best. This page summarizes the evidence RepoRadar has captured from captured source metadata. 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 Advai-X/advai-cli a composite score of 7.9 out of 10, placing it in the Silver 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 1.0 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 vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
Installing skills from GitHub and proxying external CLIs can write into agent-specific directories and execute third-party tools, so first runs should stay limited to trusted repos; Local state lives under ~/.advai and synced skills can spill across multiple runtimes, so shared machines need profile hygiene before storing work knowledge there.