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srt-title-generator
Generate engaging, viral-potential video titles from SRT subtitle files
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Generate engaging, viral-potential video titles from SRT subtitle files
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Decide whether a task in the current project is worth running as an agent loop. Analyzes the repo for evidence first (tests/CI/bench scripts = available verifiers; issue+PR queues = recurring work; module boundaries), then interviews the user one question at a time on the genuine decisions, and returns one of three verdicts — don't loop (stay in the loop yourself), timer loop (/loop, /schedule), or goal loop (/goal) — with cited evidence and, when looping is warranted, a drafted four-part contract (goal / verification / boundary / stop) bound to real commands found in the repo. Recommending NO loop is a first-class outcome. Use when the user asks 值不值得 loop / should I loop this / 要不要上 /goal / 这个活能不能挂个循环自动跑, or wants to apply loop engineering to a project.
GitHub backlog governance manager-loop. Triage open issues (type + routing labels), complete thin descriptions, maintain a bounded ready queue (Todo ≤ 5) on a GitHub Projects board, and repair board drift (closed issue still "In Progress" etc.). Config-driven — reads .claude/backlog-manager.yaml from the target repo; runs an init flow to generate it if missing. DRY-RUN by default, pass "apply" to execute writes. Use for recurring backlog grooming / issue triage of any GitHub repo, standalone or driven by /loop. Requires gh CLI with repo + project scopes.
Generate images (Nano Banana Pro / Imagen) and videos (Veo 3.1) through Google Flow using the account's Ultra/Pro SUBSCRIPTION credits instead of the metered Gemini/Vertex API — no per-call API cost. Use when the user wants to create a thumbnail, cover, poster, b-roll clip, image, or short video with AI and wants to avoid API billing, or explicitly mentions Flow / gflow / Veo / Nano Banana via subscription. Wraps the gflow-cli tool; encodes this machine's Flow new-UI quirk (PREFER_CLASSIC) and credit-safe retry rules learned the hard way. NOT for the paid Gemini-API nano-banana-pro path (that costs money) — this is the subscription path.
Generate a printer-receipt styled PNG bill of AI token usage and cost from local ccusage data, for the 绿皮火车 channel. Use when the user wants a token usage "账单"/"小票"/"收银台"/receipt/invoice, a shareable spend breakdown by model / input / output / cached / by day, or 节目素材 about token 消耗/花费. Triggers on "生成账单", "token 收据", "做张小票", "用量账单", "token receipt", "spend breakdown image".
本地把音频/视频文件或在线视频 URL 转录成文字稿(txt/srt/vtt/json)。基于 Apple Silicon 上的 mlx_whisper,支持中英文等多语言、自动语言检测、模型规格选择。当用户想要"转录""生成字幕/文稿/transcript""把这段音频/视频转成文字""提取台词""做 SRT 字幕",或给出一个音视频文件/YouTube 等链接要文字内容时使用。
Jordan Peterson(乔丹·彼得森,「龙虾教授」)的思维框架与表达方式。基于著作、长访谈/辩论 transcript、X发帖、外部批评、决策记录、完整时间线共6维度216个来源(一手占比约48%)的深度调研, 提炼6个核心心智模型、8条决策启发式和完整的表达DNA,并内置其已被外部验证的失效模式标注。 用途:作为思维顾问,用彼得森的视角分析个人困境、意义危机、责任与成长、文化争议、叙事与神话。 当用户提到「用彼得森的视角」「Jordan Peterson会怎么看」「彼得森」「皮特森」「龙虾教授」「JP模式」「JBP」 「peterson perspective」「人生十二法则」「12条法则」时使用。 即使用户只是说「整理好你的房间」「混乱与秩序」「先承担责任」 「帮我用彼得森的角度想想」「切换到彼得森」也应触发。 用户讨论「躺平」「内卷」「精神内耗」「年轻人迷茫」「人生没有意义」等话题且明确想要某种视角分析或建议时也可触发。 不要在用户只是泛泛倾诉、求安慰、查心理学概念,或寻求真实医疗/心理咨询时触发—— 这是思维框架skill,不是心理治疗。
| name | srt-title-generator |
| description | Generate engaging, viral-potential video titles from SRT subtitle files |
Generate engaging, viral-potential video titles from SRT subtitle files.
A skill that analyzes SRT subtitle/transcript files and generates compelling video titles optimized for YouTube, Xiaohongshu (小红书), and other platforms. Uses AI to identify key hooks, emotional triggers, and viral elements from the content.
Use this skill when users:
| Platform | Max Length | Style |
|---|---|---|
| YouTube | 60 chars | Hook + Keywords, 数字/问句/大胆声明 |
| 小红书 | 20 chars | 简短爆点 + emoji |
| Bilibili | 80 chars | 详细 + B站风格 |
| 抖音 | 55 chars | 悬念 + 口语化 |
When generating titles, use this analysis framework:
<scratchpad>
1. 主题识别: 从字幕中提取核心主题和关键点
2. 钩子发现: 找出最吸引人的角度或故事
3. 点击欲望: 什么会让观众想要点击
4. 草拟标题: 列出 3-5 个候选标题
5. 最优选择: 根据以下标准选出最佳:
- 吸引眼球、制造好奇
- 简洁 (YouTube ≤60字符)
- 包含相关关键词
- 准确反映内容
- 使用情绪触发词
- 避免标题党
</scratchpad>
中文:
English:
Generate output in this structure:
## 分析过程
### 核心主题
[从字幕提取的1-2句主题总结]
### 关键钩子
- 钩子1: [描述]
- 钩子2: [描述]
### 目标受众
[谁会对这个内容感兴趣]
---
## 推荐标题
### YouTube (≤60字符)
1. **首选**: [标题]
2. **备选**: [标题]
3. **备选**: [标题]
### 小红书 (≤20字符)
1. [标题 + emoji]
2. [标题 + emoji]
### Bilibili (≤80字符)
1. [标题]
2. [标题]
---
## 标题解析
[解释为什么首选标题最有效]
本期节目我们将进行一个Vibe Coding的极限挑战
你将看到我们如何用两句大白话就让Claude徒手写出一个下载播客的Skills
YouTube:
小红书:
Bilibili:
When user provides an SRT file for title generation:
Read the SRT file:
cat "path/to/file.srt"
Extract text content (remove timestamps):
Analyze and generate using the prompt framework above
Present titles in the structured format
v1.0 (Current)