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 Supreme-Ultimate/novel-to-script-team --skill storyboard-review-skillgit clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-teamWrote 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/supreme-ultimate/novel-to-script-team/storyboard-review-skill)<a href="https://agentmods.dev/skills/supreme-ultimate/novel-to-script-team/storyboard-review-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/storyboard-review-skill/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/supreme-ultimate/novel-to-script-team/storyboard-review-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/storyboard-review-skill.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 | $0.00050 | $0.01707 |
| Opus 5 | $0.00025 | $0.00853 |
| Sonnet 5 | $0.00010 | $0.00341 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
storyboard-review-skill 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
分镜审核技能
必读
../../references/00-first-principles.md../../references/04-review-gates.md../../references/05-compliance-boundaries.md../../references/09-storyboard-methodology.md
技能说明
审核影视分镜产出，包括节拍拆解表、Beat Board 九宫格提示词、Sequence Board 四宫格提示词。通过逐项比对原始剧本、脑内预演 AI 出图效果、逐项评分的方式，确保分镜质量真正达标，能通过 AI 出图工具生成符合导演意图的分镜图。
审核对象
beat-breakdown.md— 节拍拆解表beat-board.md— Beat Board 九宫格提示词sequence-board.md— Sequence Board 四宫格提示词
审核流程
第一步：建立整体理解
- 读取原始剧本
- 读取待审核的分镜产出
- 明确审核立场：你的任务是找出问题，而非确认通过
第二步：逐项比对
- 对节拍拆解：逐个检查 9 个 Beat Anchor 是否准确识别了叙事拐点
- 对 Beat Board：逐格对照节拍拆解，检查九宫格提示词是否准确传达了每个 Beat Anchor 的叙事目的和情绪
- 对 Sequence Board：逐组对照 Beat Board，检查四宫格提示词是否继承了九宫格对应格的人物/场景/光色描述
第三步：脑内预演
- 对 Beat Board：想象把九宫格提示词丢进 AI 出图工具，生成出来的九宫格图会是什么样？
- 对 Sequence Board：想象把四宫格提示词丢进 AI 出图工具（使用九宫格对应格作为参考图），生成出来的四宫格图会是什么样？
- 判断：生成的分镜图是否准确传达了原始剧本的叙事和情绪？
第四步：逐项评分
按照下方验收清单，对节拍拆解、Beat Board、Sequence Board 分别评分
第五步：输出结果
- 计算总平均分
- 平均分 ≥ 8 且无单项低于 6 → PASS
- 平均分 < 8 或任一单项低于 6 → FAIL + 问题清单
验收清单
节拍拆解（整体评分 1-10）
- □ 拐点识别准确性：9 个 Beat Anchor 是否准确识别了叙事曲线的关键拐点？是否有重要拐点被遗漏？是否有不重要的点被错误标记为拐点？
- □ 叙事目的明确性：每个 Beat Anchor 的叙事目的是否明确？是否有模糊或重复的叙事目的？
- □ 情绪标注准确性：每个 Beat Anchor 的情绪标注是否准确反映了该节点的情绪基调？
- □ 时长估算合理性：每个 Beat Anchor 的时长估算是否与其叙事密度匹配？
Beat Board 九宫格提示词（整体评分 1-10）
- □ 与节拍拆解一致性：每格提示词是否准确传达了对应 Beat Anchor 的叙事目的和情绪？
- □ 视觉规范完整性：是否包含整体风格、色彩基调、材质质感的描述？
- □ 格间风格统一性（脑内预演）：想象生成出来的九宫格图，所有格子的视觉风格是否统一？
- □ 提示词质量：每格提示词是否采用叙事描述式？是否具体到可视化程度？是否包含景别、环境、人物、动作、光线、色调、氛围？
- □ 格式可执行：整段提示词能否直接复制到 AI 出图工具生成一张完整的九宫格图？
Sequence Board 四宫格提示词（整体评分 1-10）
- □ 继承一致性：每组四宫格提示词是否继承了九宫格对应格的人物/场景/光色描述？发生变化是否有明确说明？
- □ 动作展开合理性：每组四宫格是否合理展开了对应 Beat Anchor 的段落动作？动作链是否完整连贯？
- □ 参考图指令明确性：每组四宫格是否明确标注了使用九宫格对应格作为参考图（垫图）？
- □ 提示词质量：每格提示词是否采用叙事描述式？是否具体到可视化程度？
- □ 格式可执行：每组提示词能否直接复制到 AI 出图工具（配合九宫格对应格作为参考图）生成一张完整的四宫格图？
整体连贯性（整体评估，不单独评分，但影响最终判定）
- □ 叙事连贯性：从节拍拆解 → Beat Board → Sequence Board，叙事线是否连贯？是否有断裂或跳跃？
- □ 视觉连贯性：Beat Board 九宫格和 Sequence Board 四宫格之间，视觉风格是否统一？光影逻辑是否自洽？
- □ 剪辑可行性：Sequence Board 的四宫格展开是否考虑了剪辑需求？相邻格子之间是否能自然剪接？
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 · 126 lines · 50 tokens per session scan A 199050f727b5
storyboard-review-skill is a skill published in the GitHub repository Supreme-Ultimate/novel-to-script-team (167 stars, last pushed 4mo ago), licensed MIT. It adds 50 tokens to every session and 1,707 once invoked, about $0.0003 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 2026-08-30.
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