Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for builders who want a reproducible way to fan out multi-agent work on one machine without letting every spawned agent loose on the same checkout or shell profile.
Who should use it
Who should skip it
Move on from chekusu/wanman if the licensing terms, language support, or platform requirements do not fit your project.
About this signal
chekusu/wanman is tracked by RepoRadar as a agent matrix runtime in the Developer Tools section. It was first seen on 2026-06-29 and last updated on 2026-06-29. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. The standout signals for chekusu/wanman are workflow potential (9.7) and open-source/build quality (8.4), while setup ease (6.4) 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 chekusu/wanman a composite score of 8.2 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 5.0 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 spawns real Claude Code or Codex workers that can edit files inside per-agent worktrees, so point the first run at a disposable repository instead of a sensitive checkout; The hosted wanman.ai layer adds extra cloud capabilities beyond the local open-source runtime, so keep the first evaluation on the local path if data control matters.