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将课程课件、作业文件（PDF、DOCX、Markdown、HTML、图片等）、课堂代码和历史答案格式转成简洁的大学生风格 Markdown 作业答案，并可由主 agent 按模块调度子代理解题与 review。Use when asked to complete course homework, read homework files in varied formats, match homework to lectures/slides/code, use methods taught in class, imitate previous hw*_solution Markdown style, create solution folders, decompose assignments across subagents, or generate necessary scripts, figures, or data files for homework submissions.
lecture-to-hw is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # Lecture to HW ## 工作流 1. 扫描当前课程目录。 - 优先用 `rg --files`，必要时配合 `find`、`ls` 和定向 `rg`。 - 找出作业文件、课件、课堂代码、notebook、HTML demo、数据、图片和历史 solution。 - 作业题目可能是 PDF、DOCX、DOC. 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 lecture-to-hw to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install vect-G/lecture-to-hwReview 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.
# Lecture to HW ## 工作流 1. 扫描当前课程目录。 - 优先用 `rg --files`，必要时配合 `find`、`ls` 和定向 `rg`。 - 找出作业文件、课件、课堂代码、notebook、HTML demo、数据、图片和历史 solution。 - 作业题目可能是 PDF、DOCX、DOC、Markdown、HTML、noteb