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NetEase Cloud Music Intelligent Assistant, with model judgment at its core, executes operations via ncm-cli. Core capabilities: Analyze user's liked songs playlist preference profile, develop multi-keyword search strategies, intelligently recommend playlists/albums/singles (including two-layer recommendation explanations), playback control (play/pause/next track/volume/queue), manage scheduled push tasks, push recommendation results to IM channels like Feishu via OpenClaw, create and add to playlists. Trigger conditions (activate if any is met): - Messages contain "NetEase Cloud" or "Cloud Music" - User wants to listen to music, needs playlist recommendations, or looks for certain types of music - User wants to analyze their music preferences or liked song records
Install and configure ncm-cli (NetEase Cloud Music CLI tool). Use this skill when users need to install ncm-cli, configure API Key, install mpv player, or troubleshoot installation issues.
INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
Ask about an app's requirements, explain the tradeoff between the React Native Template App and the Spezi Template Application for Apple Platforms, clone the right repository, and hand off to the cloned project's local skills and instructions.
Plan user journeys, onboarding flows, engagement strategies, and day-to-day workflows for digital health products.
Guide a user through Stanford Biodesign's needs-finding process to define, scope, and refine a rigorous health-app need statement without jumping prematurely to solutions.
Generate changelog entries from git history using Keep a Changelog structure and user-facing release language.
Plan health data concepts, entities, relationships, interoperability needs, and governance choices for digital health products.
Turn planning outputs into a milestone-based implementation plan that sequences features, maps them to available packages or modules, and hands off to a repo-local build skill.
Plan a digital health study or research protocol, including enrollment, consent, data collection, assessment schedules, study operations, and outcome measures.
Walk through the full process of building a digital health app — from defining the need through planning to implementation.
Create release notes that summarize features, fixes, and migration guidance for software releases.