youtube-long-form
The growth engine for YouTube long-form video in 2026.
What this skill does for you
The growth engine for YouTube long-form video in 2026. Use when someone asks to "grow my YouTube channel," "get more views on my videos," "plan/script a YouTube video," "improve my CTR or retention," "why did my video flop," or wants a long-form strategy. Produces packaging concepts + scripts; the human films/edits/designs the thumbnail; publishing routes through scheduling-and-queue -> WoopSocial; analytics and session features live in YouTube Studio. The opposite engine from, and sibling to, youtube-shorts.
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 youtube-long-form skill from social-media-skills/skills.
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: 6e30eeb2f6736bda8683b6bbaa674af3641d7945. 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: 6e30eeb2f6736bda8683b6bbaa674af3641d7945. 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: 6e30eeb2f6736bda8683b6bbaa674af3641d7945. Raw findings: . Counted findings: .
Source and licence
- Repository
- https://github.com/social-media-skills/skills
- Pinned skill file
- View source at revision
- Revision
- 6e30eeb2f6736bda8683b6bbaa674af3641d7945
- Package hash
- sha256:9244a89ebc3a1d034524aadbad46f77af3a5543dc7169a36144088585a2e8737
- Licence
- MIT