القائمة
Scan GitHub trending daily and report which repos contain ideas worth stealing for your project — patterns, not stars. Use for repo scouting and idea extraction.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Turn a content creator's AI stack into a factory that sounds like THEM. One voice spine (CONTENT.md) governs every format — FB/blog posts, TikTok carousels, YouTube Shorts, covers — so the output stops smelling like AI and comes out consistent every run. Use when a creator (not a dev) wants to set up Claude Code / an AI agent for content production across channels, or fix output that reads generic, breaks Thai fonts, or looks different every gen. Triggers: "setup AI for content", "brandbook for AI", "AI writes generic", "content creator claude md", "carousel/shorts pipeline", "cover generator".
Keep an AI character's face and voice identical across every clip. Lock the identity ONCE (train a face, lock a voice), then reuse it — never re-generate the face. Use when a recurring AI character drifts between clips, looks like a different person each render, or the brand face is never consistent.
Split AI content into two layers — AI generates raw material (backgrounds, characters, clips), code assembles the deliverable (text, layout, render). Use when AI-generated carousels/cards come out inconsistent, Thai fonts break, or every re-gen is a gamble.
Pump the brakes — clarify before acting. Use when a request is exploratory, mid-decision, or underspecified and the AI is about to edit, commit, hand off, deploy, or run a workflow on a partial picture. Fires on /hold-up or "just talk", "don't action this", "let's think first" — or auto-fires when the AI catches discuss-mode cues right as it was about to take a non-trivial action.
Game-theory review loop for AI drafts: tit-for-tat trust tracking across review rounds. Review depth adapts to the author's track record of addressing feedback, so clean drafts earn lighter reviews and ignored flags trigger deep audits. Use for recurring content or code review loops.
Personal commitments tracker with escalating confrontation. Use when the user wants accountability on recurring commitments, training, habits, or deadlines they keep deferring. Reviews the track record and escalates tone based on the avoidance pattern, not the excuses.
| name | steal-digest |
| description | Scan GitHub trending daily and report which repos contain ideas worth stealing for your project — patterns, not stars. Use for repo scouting and idea extraction. |
Stop scrolling GitHub trending aimlessly. Let AI scan it daily and tell you which repos have ideas worth stealing for your project.
Not copying code. Stealing ideas — seeing how someone else solved a problem and asking "can I use this pattern?"
ไปดู GitHub trending วันนี้ (https://github.com/trending) เลือก 3-5 repos ที่น่าสนใจสำหรับ stack ของผม [ระบุ stack เช่น: React, Next.js, Python, Go]
แต่ละ repo บอก:
1. ทำอะไร (1 บรรทัด)
2. มี idea/pattern อะไรที่เอามาปรับใช้กับ project ของเราได้
3. ความยากในการ implement (ง่าย/กลาง/ยาก)
ไม่ต้อง copy code ให้บอกแค่ idea + วิธีประยุกต์
ข้ามพวก: awesome lists, tutorial repos, repos ที่ต้องเปลี่ยน stack ทั้งหมด
English version:
Check GitHub trending today (https://github.com/trending) and pick 3-5 repos relevant to my stack [specify: React, Next.js, Python, Go, etc.]
For each repo:
1. What it does (1 line)
2. What idea/pattern can be adapted for our project
3. Implementation difficulty (easy/medium/hard)
Don't copy code — just describe the idea + how to adapt it.
Skip: awesome lists, tutorial repos, repos requiring full stack migration.
The real power is automation. Set up a daily scan that runs every morning:
# Daily steal digest at 09:00
0 9 * * * cd /path/to/project && claude -p "$(cat steal-digest-prompt.txt)" >> logs/steal-digest.txt
Save the prompt above as steal-digest-prompt.txt and let it run. Check the output when you have 5 minutes.
Track what you've stolen and what's pending:
# Steal Backlog
## Queued
- [ ] AI slop detection pattern (from repo X) — adapt for UI review skill
- [ ] Rate limiting middleware (from repo Y) — simpler than current setup
## In Progress
- Product evaluation framework — adapting into Product Taste skill
## Done
- Jina Reader integration — wired into link triage
- twitter-cli — wired into content scouting
Good steals have these properties:
Bad steals:
### Steal digest
When asked to run steal digest, check GitHub trending for repos relevant to my stack.
For each candidate: what it does, what to steal, implementation difficulty.
Maintain steal backlog at data/steal-backlog.md.