slides-polish
Per-page Codex review + targeted python-pptx / Beamer fixes for academic talk slides.
What this skill does for you
Per-page Codex review + targeted python-pptx / Beamer fixes for academic talk slides. Use AFTER /paper-slides (or any externally generated PPTX/Beamer) when the deck looks 'mostly OK' but the user wants a final pass that aligns visual weight with a reference, bumps PPTX fonts to projector-readable size, kills italic style leaks, fixes text-frame overflow, and catches per-slide layout drift. Trigger phrases: "polish slides", "slides 排版不对", "PPTX 字体太小", "和 Beamer 比一下", "per-page review", "和 codex 一页一页过".
Quoted from the skill description in the pinned sourceWho made it
Use it with Edge
Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the slides-polish skill from wanshuiyin/auto-claude-code-research-in-sleep.
Paste it into Claude, ChatGPT, Codex or Cursor.
Or read the skill source first.
Security evidence
| Scanner | Date | Result | Findings |
|---|---|---|---|
| Edge static checks | 2026-09-27 | Pass | 0 |
| Cisco skill-scanner | 2026-09-27 | Pass | 0 |
| Semgrep Edge rules | 2026-09-27 | Pass | 0 |
Static scans check the code, not how well the skill works.
Scanner scope, raw findings and mirrored provider records
Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 341f914024d270dc5c8fa51337d1ad38829273aa. Raw findings: . Counted findings: .
Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 341f914024d270dc5c8fa51337d1ad38829273aa. Raw findings: 1. Counted findings: .
Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 341f914024d270dc5c8fa51337d1ad38829273aa. Raw findings: . Counted findings: .
Source and licence
- Repository
- https://github.com/wanshuiyin/auto-claude-code-research-in-sleep
- Pinned skill file
- View source at revision
- Revision
- 341f914024d270dc5c8fa51337d1ad38829273aa
- Package hash
- sha256:120cc83b46ef2f07db2d536e3067b6a33a71f481be0244d8ad79c90eec6e17dd
- Licence
- MIT