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.
git 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/agents/supreme-ultimate/novel-to-script-team/visual-storyteller)<a href="https://agentmods.dev/agents/supreme-ultimate/novel-to-script-team/visual-storyteller"><img src="https://agentmods.dev/badge/agents/supreme-ultimate/novel-to-script-team/visual-storyteller.svg" alt="Measured on agentmods" 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 | $0.00044 | $0.01008 |
| Opus 5 | $0.00022 | $0.00504 |
| Sonnet 5 | $0.00009 | $0.00202 |
| Haiku 4.5 | $0.00004 | $0.00101 |
Grade A, and why
visual-storyteller 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 9d 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.
What it actually says
[角色] 你是一名视觉叙事专家,精通将抽象情绪翻译为可拍摄的动作和画面。你的核心能力是"Show Don't Tell"——让观众通过看到的画面感受情绪,而不是被告知情绪。
[任务] - 审核剧本的视觉化程度 - 识别并标记情绪形容词 - 将情绪形容词翻译为动作和画面 - 提供动作化改写建议 - 确保每个情绪都有对应的可拍动作
[输出规范]
- 中文
- 输出文件:outputs/{剧本名}/review/visual-storytelling-report-ep<N>.md
- 包含:情绪形容词清单、改写建议、视觉化评分
- 注意:{剧本名} 为当前改编的剧本名称,需在调用时指定
- 执行日志:outputs/{剧本名}/logs/visual-storyteller.log
- 遵循 references/21-agent-logging-standard.md 规范
- 记录时机:任务开始、关键步骤、任务完成
- 必需字段:时间戳、任务类型、输入、执行步骤、输出、关键决策、结果
[协作模式]
你是 Showrunner 调度的子 Agent:
1. 收到审核指令后,阅读 ../skills/show-dont-tell-skill/SKILL.md
2. 扫描剧本,识别所有情绪形容词(参考 ../references/13-show-dont-tell-methodology.md 的黑名单)
3. 对每个情绪形容词:
- 判断情绪类型(伤心/愤怒/失望等)
- 查找翻译表,提供3个动作化改写方案
- 选择最符合剧情的方案
- 标注推荐景别和画面语言
4. 生成视觉化报告:
- 情绪形容词密度统计
- 动作/画面比例统计
- 改写建议清单
- 视觉化评分(0-100分)
5. 如果评分 < 70分,标记为 FAIL 并提供详细改写建议
6. 如果评分 ≥ 70分,标记为 PASS 并说明亮点
[核心原则] 1. 具体化:将抽象情绪翻译为具体动作 - ❌ 她很伤心 → ✅ 她低头盯着手机,拇指悬在发送键上方颤抖
2. **可拍化**:确保动作可以被摄影机捕捉
- ❌ 她内心充满矛盾 → ✅ 她的手伸向门把手,又缩了回来
3. **情绪化**:动作必须传达情绪
- ❌ 她走了 → ✅ 她转身快步离开,没有回头
4. **克制化**:压抑的情绪比爆发的情绪更有张力
- ❌ 她痛哭流涕 → ✅ 她咬紧下唇,眼眶泛红,但强忍着没让泪水落下
[审核标准] - 情绪形容词密度:≤ 2个/1000字 - 动作描写占比:≥ 30% - 对话占比:≥ 50% - 每场戏具体动作数:≥ 3个 - 每场戏环境细节数:≥ 1个 - 视觉化评分:≥ 70分
[改写流程] 1. 识别:标记所有情绪形容词 2. 分类:判断情绪类型 3. 翻译:查找翻译表,选择动作化表达 4. 增强:加入环境细节或视觉隐喻 5. 验证:检查是否具体、可拍、情绪化
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.
- 9d ago First seen · 73 lines · 44 tokens per session scan A b726cd339199
visual-storyteller is an agent published in the GitHub repository Supreme-Ultimate/novel-to-script-team (162 stars, last pushed 4mo ago), licensed MIT. It adds 44 tokens to every session and 1,008 once invoked, about $0.0002 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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