基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/TheMattBerman/scrollclaw --skill scrollclaw-score命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
One-time brand initialization. Given a brand name and URL, researches the brand and generates the three workspace/brand/ files that the rest of the pipeline reads. Run once per brand before any campaign work.
Router and orchestrator for AI UGC video production. Use for broad outcome requests like making a UGC video or running a campaign; it routes step-specific requests to the right sub-skill and can drive the full pipeline from persona research through virality-scored video.
ScrollClaw system — core doctrine, format selection, pipeline routing, and anti-patterns. Loaded into every UGC conversation.
| name | scrollclaw-score |
| description | Score UGC videos for virality before publishing. 7 criteria, 0-100 each. Only 70+ gets published. |
| metadata | {"openclaw":{"emoji":"📊","user-invocable":true,"triggers":["score video","virality score","ugc score","rate ugc","video quality check"]}} |
Score every video before publishing. Read references/virality-scoring.md for the full methodology.
7 dimensions, scored 0-100 each:
| Score | Action |
|---|---|
| 70+ | Publish. Ship it. |
| 60-69 | Polish — specific fixes can save it. Identify which dimensions are dragging. |
| Below 60 | Regenerate. Don't polish a bad clip. Go back to the failing stage. |
/first-frame (regenerate canonical face)/persona (restructure script)/persona (better language from research)/assemble (fix captions)/assemble (re-run S2S)| File | Purpose |
|---|---|
workspace/campaigns/<slug>/clips/final-*.mp4 | Video(s) to score |
workspace/campaigns/<slug>/brief.md | Original campaign goals — score against intent, not just virality |
workspace/campaigns/<slug>/persona-research.md | Whether the script language matches real customer language |
| File | Notes |
|---|---|
workspace/campaigns/<slug>/scores/score-<version>.md | Score card with per-dimension breakdown and go/no-go |
workspace/campaigns/<slug>/learnings.md | Append-only — what worked, what didn't, threshold notes |
📊 Score context loaded:
✓ Campaign: ridge-q1
✓ Final clips: 2 (workspace/campaigns/ridge-q1/clips/final-*.mp4)
✓ Brief: workspace/campaigns/ridge-q1/brief.md
✓ Persona research: workspace/campaigns/ridge-q1/persona-research.md
After every score, append to workspace/campaigns/<slug>/learnings.md:
## YYYY-MM-DD — <campaign-slug> <format>
**Score:** <average>/100 (<go/no-go>)
**Dimension breakdown:** Hook <n> | Emotional <n> | Pacing <n> | Captions <n> | Scroll-stop <n> | Completion <n> | Share <n>
**What worked:**
- [specific finding]
**What didn't:**
- [specific finding]
**Remediation:** [if no-go: which skill to route back to and why]
Never overwrite this file. Only append.
/assemble, workspace/campaigns/<slug>/brief.md, and persona-research.mdworkspace/campaigns/<slug>/scores/ plus append-only entries in learnings.mdworkspace/campaigns/<slug>/scores/score-<version>.mdworkspace/campaigns/<slug>/learnings.mdFor campaign batches, score all variants and rank. Publish only the 70+ tier. Below-60 variants get regenerated, not tweaked.
bash scripts/batch-campaign.sh \
--workspace workspace/campaigns/<slug> \
--creators workspace/campaigns/<slug>/creators/ \
--formats "talking-head,pov-demo,podcast-clip" \
--dual-output