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 zenstory-ai/oh-story-dsh --skill video-scriptgit clone --depth 1 https://github.com/zenstory-ai/oh-story-dshWrote 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/zenstory-ai/oh-story-dsh/video-script)<a href="https://agentmods.dev/skills/zenstory-ai/oh-story-dsh/video-script"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-dsh/video-script/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/zenstory-ai/oh-story-dsh/video-script"><img src="https://agentmods.dev/badge/skills/zenstory-ai/oh-story-dsh/video-script.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 | $0.00309 | $0.05303 |
| Opus 5.5 | $0.00124 | $0.02121 |
| Sonnet 5.5 | $0.00062 | $0.01061 |
| Haiku 4.5 | $0.00031 | $0.00530 |
Grade A, and why
video-script 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- video-script — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1. 定位
只改宣发标题、封面、花字或回填外部文案时,直接读 references/promotional-copy.md,
按当前短片的观看理由和兑现位置处理指定文字层,不重做下述策划/旁白链。
普通解说写作不因此增加平台调研或包装任务。
本技能负责创作方向、画面与声音计划、旁白写作及校验。Agent 依次从以下五个角度作出决定:
- 导演
- 故事编辑
- 画面剪辑师
- 声音/旁白编辑
- 第一次观看的观众
Agent 先记录简洁决定,再写时间线产物。validate.py 负责对理解索引做机械校验,从不改写 Agent 的稿子:段落顺序、数量、时间、文本、停顿和扩展元数据原样保留,只依据现有声音证据回写实测的 overlaps_speech。文本装不下时间窗、段落未按时间排序等问题以 error 退回给 Agent 修改。
下面的 scripts/... 均相对于本技能目录。若执行器从仓库根目录启动,请给脚本路径加上本技能的绝对目录。
1.1 创作控制模式
先根据用户要求和 work_dir 判断本轮创作控制模式。它与 full|cut|dub 渲染模式分别选择:
- CREATE:首次创作。比较至少两个真正可行的故事/剪辑假设后再选择。
- DIRECTED:用户已指定结构、镜头、台词或表达。忠实落实,不为满足“创作流程”虚构替代方案。
- REVISION:用户针对已有版本看片修改。最新反馈是当前事实来源;未点名部分默认冻结。
REVISION 先明确本轮修改项与冻结项,再编辑对应层:表达、口语节奏、字幕反馈更新 style_card.json;镜头、入出点、表演和声音分工更新 visual_audio_board.json;只有观众承诺、POV、主线或 beat 改变时才更新 recap_story_plan.json。被删除的镜头、原声或文案也要从相关计划中删除,不能保留过期锚点。不要把看片修改重新做成一次 CREATE。
2. 远程调用与数据外发
本技能只有一个脚本会联网:review.py(§7.1 的建议型语义评审)。其余全部在本地运行:validate.py 及其 lint、去 AI 味检查只读写 work_dir 里的文件,不发任何网络请求;策划与写稿由 Agent 直接读写 work_dir 完成。
review.py 发给谁:
- MiMo 的 OpenAI 兼容 chat 接口
<MIMO_API_URL>/chat/completions,用MIMO_API_KEY认证,模型为MIMO_MODEL(默认mimo-v2.5)。未设MIMO_API_URL时,按量计费 key 发往https://api.xiaomimimo.com/v1,tp-开头的 Token Plan key 发往MIMO_TOKEN_PLAN_CLUSTER选定的 token-plan 集群(默认https://token-plan-cn.xiaomimimo.com/v1)。 - 未设
MIMO_API_KEY时直接退出,不构造也不发送任何请求。
review.py 发送什么(只有文字,不发视频、帧图片或音频文件):
narration.json全部旁白段的时间与文字。- 理解索引的文字证据:开头、中段、结尾、长空档与各旁白时间窗附近选出的时间段内,
vlm_analysis.json的场景描述与frame_facts文字,以及对白转写(有asr_clean.json时用它,否则asr_result.json)。 background_research.json的梗概、角色、关系与剧情线摘录。- 存在时附上
packaging_plan.json、recap_story_plan.json、visual_audio_board.json、style_card.json(各截前 3000 字)和original_subtitles.json的原声字幕文字。 - 内容较长时分块,每块一次请求;返回的意见只写回本地
narration_review.json/narration_review.md。
何时运行、怎样关闭:
- 单独使用本技能时,
review.py只在用户或 Agent 显式执行它时运行;不执行它就没有任何外发。用户不希望稿件离开本机时,不要运行它,改为人工复核后直接跑validate.py。 - 端到端编排默认在 TTS 前自动调用一次这项评审,失败不阻断;关闭方式是编排入口的
--no-review-narration或环境变量REVIEW_NARRATION=0。若同时开启了严格评审(--require-narration-review或REQUIRE_NARRATION_REVIEW=1),评审必须运行,关闭开关不生效。 - 评审是建议型的:只写报告,从不改写
narration.json;是否修改由 Agent 或用户决定。
What ships with it
16 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.
- references/creative-editing-playbook.md 14 KB
- references/promotional-copy.md 5.0 KB
- references/research-guide.md 3.1 KB
- scripts/agent_text.py 2.0 KB runs code
- scripts/deslop_qc.py 9.3 KB runs code
- scripts/entry_suggestion.py 4.9 KB runs code
- scripts/evidence_bundle.py 13 KB runs code
- scripts/lib.py 12 KB runs code
- scripts/lint_summary.py 8.1 KB runs code
- scripts/narration_lint.py 29 KB runs code
- scripts/review_grounding.py 8.2 KB runs code
- scripts/review_response.py 25 KB runs code
- scripts/review_runner.py 7.1 KB runs code
- scripts/review.py 157 B runs code
- scripts/speech_ownership.py 8.7 KB runs code
- scripts/validate.py 6.3 KB runs code
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 Changed · -9 lines 02f231df44d6
- 19d ago Changed · +27 lines · +119 tokens per session 7ae12d12f77e
- 24d ago Changed · +2 lines 387b8e7f57c1
- 29d ago Changed · +3 lines · +36 tokens per session bec6a27c499b
- 1mo ago First seen · 249 lines · 154 tokens per session scan A 58d03a784e81
video-script is a skill published in the GitHub repository zenstory-ai/oh-story-dsh (629 stars, last pushed today), licensed MIT. It adds 309 tokens to every session and 5,303 once invoked, about $0.0012 per session on Opus 5.5. 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 2026-09-05.
Other skills, from other repositories
story-deslop
A writing editor for Chinese web novels that detects writing patterns often associated with AI-generated text and makes the prose feel more natural.
story-long-analyze
A long-form fiction analysis workflow for breaking down a novel’s opening chapters, characters, pacing, turning points, relationships, and overall structure.
browser-cdp
Use this skill when you need to control a Chrome browser via CDP (Chrome DevTools Protocol) to reuse existing login sessions. Covers: launching Chrome in debug mode, opening URLs, waiting for page load, evaluating JavaScript, taking snapshots, and extracting auth tokens. Trigger phrases: browser automation, CDP…
workflow-manager
A writing workflow tracker for chapter-based projects. It records whether each chapter is being assembled, drafted, reviewed, confirmed, polished, or archived.
review-chapter
A six-part review of a manuscript chapter. It compares the chapter with the outline and reports quality, coverage, review status, and problems supported by evidence from the text.
revise-span
A revision workflow for changing selected passages in a manuscript. It shows the original and proposed text, then applies changes only after the author confirms them.