Course Study
/install course-study
Course Study v2.0
A structured four-phase workflow for deep learning of any university or college course: Extract → Synthesize → Expand → Study. Produces high-fidelity, multi-format study materials as a single, complete PDF — not shallow summaries.
Phase 0: Intake
Read rules/phase-intake.md and run the full intake workflow. Keep this to one exchange — do not ask questions across multiple messages.
Workflow
Phase 0: Intake (single exchange)
├── PDFs → Phase 1 (Extract via /pdf skill)
├── Topic list → Phase 2 directly
└── Course name → quick syllabus search → Phase 2
Phase 1: Extract (per PDF, page-aligned, using /pdf skill)
└── Output: lecture-XX-extract.md
Phase 2: Synthesize
└── Output: course-synthesis.md
Phase 3: Expand (web sources OR curriculum-grounded)
└── Output: course-expansion.md
Phase 4: Study Materials
├── study-notes.md (always)
├── quick-reference.md (Exam Ready only)
└── exam-qa.md (Exam Ready only)
Each phase ends with a brief checkpoint (see below).
Phase Checkpoint
After each phase, one compact message:
✓ Phase [X] done — [summary in one line].
Issues? (coverage gaps / too shallow / too verbose)
Type to adjust, or just say "continue".
If no response issues → proceed immediately. No multi-question forms.
Global Rules
-
PDF-only input. Use the
/pdfskill to read all course files. Do not use Python file I/O or direct file reading for PDFs. -
Backbone fidelity. Every concept traces back to its source: page number (PDF) or section number (topic list). Never lose traceability.
-
Speed discipline. Minimize round-trips. Batch questions. Skip steps that aren't needed for the current tier. Phase 1 and 2 intermediate files should be dense and compact — no padding, no repeated meta-commentary.
-
No fabrication. Phase 3 without web access: every claim marked
[Standard curriculum knowledge]. No invented URLs, paper titles, or authors. -
Examples are mandatory. Phase 4 must include worked examples for every non-trivial concept.
-
Track progress. Use TodoList to track which lectures have been processed.
-
Multi-format output. Final notes are written in format-agnostic Markdown per
rules/templates.md. When the user requests PDF output, readrules/pdf-export.mdfor pandoc font configuration and CJK handling before converting. -
Prioritise flagged topics. If the user named priority topics in Phase 0, give them deeper treatment in Phase 4 and ensure they appear in the Quick Reference and Exam Q&A.
Phase 4 Output: Study Notes
The main study notes follow the structure in rules/phase-study.md. Every concept gets:
- What it is — definition, instructor's phrasing first
- Intuition — why it exists, what problem it solves
- Formal treatment — LaTeX formulas or code blocks
- Worked example — concrete, step-by-step
- Connections — prerequisites and what this enables
- Common misconceptions
Exam Ready appendices (Quick Reference Sheet and Exam Q&A) are generated in Phase 4 as well — see rules/phase-study.md Steps 6a and 6b.
Reference Files
rules/phase-intake.md— Phase 0 intake workflowrules/phase-extract.md— Phase 1rules/phase-synthesize.md— Phase 2rules/phase-expand.md— Phase 3rules/phase-study.md— Phase 4 (study notes + Exam Ready appendices)rules/templates.md— Format-agnostic writing rulesrules/pdf-export.md— PDF conversion config (load only when PDF output is requested)rules/subject-coverage.md— Live search strategy for curriculum gap analysisrules/changelog.md— Version history
Anti-Patterns
| Avoid | Why | Instead |
|---|---|---|
| Skipping worked examples | Students fail on application, not definitions | Mandatory for every non-trivial concept |
| Quick Reference with prose | Defeats the purpose | One line per entry maximum |
| Exam Q&A without source refs | Student can't verify or dig deeper | Every answer cites source location |
| Ignoring Phase 0 priority topics | User told you what matters | Deeper treatment + appears in all appendices |
| Fabricating exam question styles | Misleads preparation | Draw only from what the course actually covers |
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install course-study - 安装完成后,直接呼叫该 Skill 的名称或使用
/course-study触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Course Study 是什么?
Comprehensive course study, exam revision, and structured study note generation from lecture slides, course PDFs, or topic outlines. Use when the user wants... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 600 次。
如何安装 Course Study?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install course-study」即可一键安装,无需额外配置。
Course Study 是免费的吗?
是的,Course Study 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Course Study 支持哪些平台?
Course Study 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Course Study?
由 VincentJiang06(@vincentjiang06)开发并维护,当前版本 v2.0.0。