visual-storyteller

visual-storyteller is an agent for Claude Code from Supreme-Ultimate/novel-to-script-team. It costs 44 tokens per session (1,008 once invoked), scanned A, original, MIT.

A specialist agent for turning written emotions into visible actions and camera-friendly details. It follows the “show, don’t tell” writing principle, which means showing feelings through what characters do instead of simply naming the feelings.

In plain words
What is it for?
Use it to review a screenplay, identify emotion words, and suggest physical actions, shots, and visual details for each one. It produces a visual-storytelling report with scoring and rewrite suggestions.
Why use it?
It helps screenplays avoid vague emotional descriptions that are difficult to film. It also makes emotional moments more concrete and easier for viewers to experience.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Good fit Use it to review a screenplay, identify emotion words, and suggest physical actions, shots, and visual details for each one. It produces a visual-storytelling report with scoring and rewrite suggestions.

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Install with agentmods
npx agentmods add agents/supreme-ultimate/novel-to-script-team/visual-storyteller
Install

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.

Clone the repo
git clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-team

Made for: Claude Code.

Wrote 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.

agentmods badge for visual-storyteller

README.md
[![agentmods](https://agentmods.dev/badge/agents/supreme-ultimate/novel-to-script-team/visual-storyteller.svg)](https://agentmods.dev/agents/supreme-ultimate/novel-to-script-team/visual-storyteller)
Your own site
<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>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,008 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash b726cd339199, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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.

agents/visual-storyteller.md · 73 lines

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

Changes

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.

  1. 9d ago First seen · 73 lines · 44 tokens per session scan A b726cd339199

Subscribe to this mod's changes

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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