Uvx skill-mgr install -t Claude -t codex

Hacker News

I built skill-mgr to solve the mess of managing agent skills. Here are the highlights: * Cross-Agent Sync: Atomically install or update a skill across multiple heterogeneous agents (Claude, Codex, Orcheo, etc.) with a single command. * Local & GitHub Sources: Install from a local directory for development or use GitHub shorthand (owner/repo/path) to treat repositories as a live skill registry. * Full Lifecycle Management: A familiar CLI surface for your agent capabilities: install, update, uninstall, list, show, and validate. * Unified Observability: skill-mgr list provides a single source of truth for your system's "agent surface area" across all supported platforms.

Visit product View on Hacker NewsApr 23, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, claude · Missing: mac, macos, cursor

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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