Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for developers who want to keep using Claude Code's native workflow while separating accounts, providers, and model costs across different profiles.
Who should use it
Who should skip it
Skip sasdsamatt123/claudex unless the captured evidence suggests it solves a problem you are actively working on.
About this signal
sasdsamatt123/claudex is tracked by RepoRadar as a developer tool in the Coding Agents 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. Across RepoRadar's eight signals, sasdsamatt123/claudex is strongest on workflow potential (9.3) and open-source/build quality (8.4) and weakest on maturity (5.7) — a profile worth weighing against your own priorities. 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 sasdsamatt123/claudex a composite score of 7.8 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
It stores multiple API keys and profile configs locally, so the first setup should use dedicated low-spend test credentials and confirm where secrets land on disk; Anthropic-compatible providers can differ on tool support, context handling, and model behavior, so workflows should be tested per provider instead of assuming full Claude Code parity.