Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add handsomeng/Hskill-chatcut --skill publish-video-three-platformsgit clone --depth 1 https://github.com/handsomeng/Hskill-chatcutWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/handsomeng/hskill-chatcut/publish-video-three-platforms)<a href="https://agentmods.dev/skills/handsomeng/hskill-chatcut/publish-video-three-platforms"><img src="https://agentmods.dev/badge/skills/handsomeng/hskill-chatcut/publish-video-three-platforms/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/handsomeng/hskill-chatcut/publish-video-three-platforms"><img src="https://agentmods.dev/badge/skills/handsomeng/hskill-chatcut/publish-video-three-platforms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00102 | $0.02915 |
| Opus 5 | $0.00051 | $0.01458 |
| Sonnet 5 | $0.00020 | $0.00583 |
| Haiku 4.5 | $0.00010 | $0.00292 |
Grade A, and why
publish-video-three-platforms scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
三平台视频发布
把已经验收的本地视频准备到小红书、抖音和微信视频号。先理解视频，再为每个平台独立生成标题、正文和话题。上传可以重叠，上传后的填写和验收严格单平台串行。最终操作默认归用户，停在最终发布按钮前。
前置要求
- 只处理用户已经确认完成的视频。
- 使用用户指定的本地 MP4 或 MOV 文件。
- 使用用户已经登录的平台页面。执行前完整读取浏览器控制 Skill。
- 不读取或保存 Cookie、密码、Token、本地存储和浏览器凭证。
- 设置
final_action_owner: user和final_click_authorized_current_turn: false作为每个任务的默认值。 - 普通的“发布到三平台”“把三个平台搞完”等表述只授权准备发布，禁止点击最终按钮。
- 只有用户在当前任务中明确说“现在直接点击发布”“现在直接点击发表”等同义指令，才设置
publish.mode: publish_now、final_action_owner: agent和final_click_authorized_current_turn: true。历史授权、定时要求和无人值守要求均不能替代当前任务授权。
固定入口
- 小红书：
https://creator.xiaohongshu.com/publish/publish?source=official - 抖音：
https://creator.douyin.com/creator-micro/content/upload?enter_from=dou_web - 视频号：
https://channels.weixin.qq.com/platform/post/create
核心原则
- 内容驱动：标题、正文和话题必须来自本期视频，不使用固定文案包。
- 平台适配：三个平台分别创作，禁止机械复制同一份文本。
- 事实忠实：不得添加视频没有表达的经历、数据、结论或承诺。
- AI 推理：先分析内容和受众，再决定标题角度、正文结构和话题组合。
- 上传重叠：依次启动三个平台上传，让网络等待互相重叠。
- 串行收尾：上传完成后的填表、话题、定时、原创或声明和审核严格一次只处理一个平台。
- 失败隔离：一个平台卡顿时保存其状态，再串行处理下一个平台。
- 证据验收：重新读取页面结果，点击记录本身不算成功。
开始前读取：
- references/content-generation.md：内容理解和平台化文案方法
- references/job-and-adapters.md：任务状态、适配器契约和恢复方法
- references/platform-interaction-signals.md：仅在当前页面快照匹配时使用的平台低自由度交互信号
标准流程
1. 分析视频
- 确认视频路径、文件名、大小、时长和可播放状态。
- 优先读取最终剪辑对应的转录稿。没有转录稿时，对视频转录或提取可理解的内容信息。
- 提炼内容简报：主题、目标受众、核心观点、关键证据、冲突、结果、语气和行动建议。
- 识别视频明确出现的专有名词、数字、品牌、人物和风险表述。
- 内容理解不足时先补充分析，禁止只根据文件名编写发布文案。
2. 生成平台文案
根据内容简报分别生成三套内容：
- 一个符合平台限制的标题或短标题
- 一段符合平台阅读习惯的正文
- 3 至 5 个与视频直接相关的话题候选，或采用平台当前允许的数量
生成后执行语义核对：
- 标题准确概括视频最值得点击的真实信息。
- 正文包含视频的核心价值，不提前泄露全部内容，也不制造虚假悬念。
- 话题覆盖主题、受众、场景和细分领域，删除与内容无关的泛流量词。
- 三个平台的表达角度可以不同，核心事实必须一致。
- 用户提供了标题或正文时优先保留其意图，只做平台适配和长度调整。
3. 创建任务状态
为本次任务创建非敏感状态记录。可以保存在当前工作区的：
.agent-state/publish-video-three-platforms/<job_id>.json
记录视频路径、生成文案、active_platform、平台步骤、验证证据和错误。active_platform 默认是 null。每个平台从任务创建起明确记录 final_button_clicked: false。禁止保存凭证。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 196 lines · 102 tokens per session scan A 57292e86eec3
publish-video-three-platforms is a skill published in the GitHub repository handsomeng/Hskill-chatcut (6 stars, last pushed 1mo ago), licensed MIT. It adds 102 tokens to every session and 2,915 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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