Loading…
28天效果追踪，对比分析皮肤变化，生成改善报告。实现追踪功能时使用此技能。
effect-tracking is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 51/100. # 效果追踪技能 ## 概述 记录用户28天护肤旅程，通过AI对比分析皮肤变化，生成可分享的改善报告。 ## 追踪周期设计 ``` Day 0 (基准) → Day 7 → Day 14 → Day 21 → Day 28 (结束) ↓ ↓ ↓ ↓ ↓ 拍照 拍照 拍照 拍照 拍照 分析 对比 对比 对比 总结报告 `. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding effect-tracking to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install David-Li0406/meta-skill-evlovingReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
# 效果追踪技能 ## 概述 记录用户28天护肤旅程，通过AI对比分析皮肤变化，生成可分享的改善报告。 ## 追踪周期设计 ``` Day 0 (基准) → Day 7 → Day 14 → Day 21 → Day 28 (结束) ↓ ↓ ↓ ↓ ↓ 拍照 拍照 拍照 拍照 拍照 分析 对比 对比 对比 总结报告 ``` ## 数据模型 ```swift