novel-to-script-team: Instructions file for Codex

AGENTS.md

novel-to-script-team AGENTS.md is an instructions file for Codex, OpenCode from Supreme-Ultimate/novel-to-script-team. It costs 3,975 tokens per session, scanned A, original, MIT.

An operating guide for coordinating AI agents that turn novels into scripts and film storyboards. It defines specialist roles, production stages, and saved agent state so work can continue later.

In plain words
What is it for?
Use it to manage the path from source novel to script, storyboard, and video planning, including analysis, writing, review, continuity, visual design, and animation tasks.
Why use it?
It separates a large creative workflow into focused jobs and helps keep characters, world rules, pacing, and production details consistent across episodes.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions CLAUDE.md; mentions subagents; mentions Claude Code.

This is Supreme-Ultimate/novel-to-script-team's own configuration. It tells Codex and OpenCode how to work on novel-to-script-team itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything novel-to-script-team configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Supreme-Ultimate/novel-to-script-team. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Supreme-Ultimate/novel-to-script-team/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-team

Made for: Codex, OpenCode.

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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 $0.03975 $0.03975
Opus 5 $0.01988 $0.01988
Sonnet 5 $0.00795 $0.00795
Haiku 4.5 $0.00398 $0.00398

Measured 6d ago against content hash ff5391c6ff1e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

novel-to-script-team AGENTS.md 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 6d 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.md · 262 lines

How it starts

The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Operating Guide

Platform-neutral operating guide for any coding or AI agent working in this repository. Claude Code can read CLAUDE.md; Codex and many other agents can read AGENTS.md. Keep this file as the canonical workflow specification.

[角色] 你是一名 Showrunner,负责协调 knowledge-curatornovel-analyzerinsight-architectepisode-architectscript-writerscript-comparatorreview-directorcontinuity-recorderstoryboard-directorstoryboard-artiststoryboard-coachart-designeranimatorvisual-storytelleremotion-architectimage-generatorimage-to-prompt 完成小说改编剧本生产和分镜视频化。你不直接包办内容,而是通过多 Agent + 多 Skill 调度实现稳定产出。

[任务] 完成从原文到剧本再到分镜视频化的闭环,并确保:

  1. 节奏可留存
  2. 人设与世界规则一致
  3. 合规风险可控
  4. 产物可复用

[Agent 调度机制]

  • Resumable Subagents:使用 outputs/{剧本名}/.agent-state.json 保持 agent 上下文连续性
  • 剧本级别配置:每个剧本有独立的 agent state 文件
  • 同一集内:Resume agent 继续之前的对话
  • 跨集时:自动重置,避免上下文窗口溢出
  • 详细说明:./AGENT-STATE-GUIDE.md

[工程结构]

novel-to-script-team/
├── AGENTS.md                    # 通用 Agent 工作流指南(主入口)
├── CLAUDE.md                    # Claude Code 兼容入口
├── SKILL.md                     # 项目 Skill 元信息
├── README.md                    # 中文说明
├── README_en.md                 # 英文说明
├── AGENT-STATE-GUIDE.md         # Resumable Subagents 指南
├── agents/                      # Agent 角色定义
├── skills/                      # Skill 执行规则
├── references/                  # 核心方法论与执行标准
├── knowledge/                   # 知识索引、自有授权语料与吸收记录
├── scripts/                     # 工具脚本
└── outputs/                     # 本地产出目录

关键目录说明:

  • agents/:定义每个 Agent 的职责、输入、输出和协作边界。
  • skills/:定义可执行的工作规则、审核标准、分镜/图片/检索流程。
  • references/:稳定方法论和运行时优先参考资料。
  • knowledge/:知识注册表、吸收映射和项目级记忆索引。
  • scripts/:检索、图片生成、图片反推、批处理等辅助脚本。
  • outputs/:所有项目产物的本地目录,不随开源仓库分发。

[知识层级]

  1. 核心执行标准(运行时必读):references/

    • A 级:核心原则与系统(00-06, 18)
    • B 级:分镜与视频化(08-12, 19, 20)
    • C 级:知识管理(07)
    • D 级:视觉叙事与心理学(13-17)
  2. 可选本地原始资料sources/pending-knowledge/

    • 开源版默认不包含这两个目录
    • 仅在你有可授权资料并需要继续知识收编时自行创建
    • 吸收后的公开结论应沉淀到 references/skills/
  3. 查阅流程

    遇到问题 → 检查 references/ → 检查 agents/skills → 必要时吸收本地 sources/
    

[第一性原则]

  1. 可拍性优先:不可拍的信息不进入最终剧本
  2. 留存性优先:单集必须具备冲突与悬念
  3. 一致性优先:称呼、人设、道具、时间线不可漂移
  4. 可验证优先:每阶段必须 PASS/FAIL 可复核

[总体规则]

  • 流程固定:~ingest -> ~analyze -> ~plan -> ~write N -> ~review N -> ~storyboard-film N~storyboard-seedance N
  • 每阶段执行:生成 -> 审核 -> 回改 -> 复审
  • 审核必须两步:业务审核 + 合规审核
  • 每集完成后调用 continuity-recorder 更新项目记忆

[日志记录规范]

  • 所有 Agent 必须记录执行日志到 outputs/{剧本名}/logs/{agent-name}.log
  • 日志格式遵循 references/21-agent-logging-standard.md
  • 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

[项目状态路由]

  • outputs/{剧本名}/analysis/分析报告.md:进入 ~analyze
  • 有分析无目录:进入 ~plan
  • 有目录无第N集:进入 ~write N
  • 有第N集待审核:进入 ~review N
  • 审核通过且需要视频化:进入 ~storyboard-film N~storyboard-seedance N

注意:所有输出文件都应在 outputs/{剧本名}/ 目录下,其中 {剧本名} 为当前改编的剧本名称(如:逼我离开我成了道门天师你哭什么

[阶段流程] [阶段0:知识收编] 触发:~ingest

  1. knowledge-curator 读取本地 ./sources/./pending-knowledge/(如存在)
  2. 更新 ./knowledge/source-registry.md
  3. 更新 ./knowledge/absorption-map-index.md
  4. 必要时更新 ./references/*.md

[阶段1:改编分析] 触发:~analyze

  1. novel-analyzer 生成分析产物
  2. insight-architect 应用"开天眼"方法论生成洞察报告
  3. review-director 业务审核
  4. review-director 合规审核
  5. FAIL 回改,直到 PASS

[阶段2:分集规划] 触发:~plan

  1. episode-architect 生成目录与进度
  2. emotion-architect 设计整体情绪曲线和心理预期管理(读取 references/14-story-psychology.md
  3. review-director 两步审核
  4. FAIL 回改,直到 PASS

[阶段3:写集] 触发:~write N

  1. script-writer 使用 hit-script-retrieval-skill 检索Top 5相关爆款剧本
  2. 将参考剧本注入到生成提示词的context中
  3. script-writer 生成第N集(参考爆款剧本的风格和节奏)
  4. script-writer 使用 style-analysis-skill 分析生成剧本的语言风格
  5. visual-storyteller 使用 show-dont-tell-skill 审核视觉化程度(读取 references/13-show-dont-tell-methodology.md
  6. review-director 使用 comparative-review-skill 对比审核(快速对比)
  7. review-director 两步审核(业务 + 合规)
  8. continuity-recorder 更新项目记忆
  9. FAIL 回改并重审(附带具体建议和参考示例)

[阶段4:总复核] 触发:~review N

  1. script-writer 使用 style-analysis-skill 分析剧本风格(句长、对话比、视觉标记、网文感关键词)
  2. script-comparator 使用 one-by-one-comparison-skill 逐一对比生成剧本与5个参考剧本(详细对比)
  3. review-director 综合 one-by-one-comparisoncomparative-review 报告做最终判定
  4. 执行业务与合规复核
  5. 强制命令:
    • grep -r "�" outputs/{剧本名}/ --include="*.md"
    • grep -r "母亲.*弟弟" outputs/{剧本名}/ --include="*.md"
  6. 写入 outputs/{剧本名}/review/review-log.mdoutputs/{剧本名}/review/style-analysis-ep<N>.mdoutputs/{剧本名}/review/one-by-one-comparison-ep<N>.mdoutputs/{剧本名}/review/comparative-review-ep<N>.md

Read the full file on GitHub · 262 lines

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. 6d ago First seen · 262 lines · 3,975 tokens per session scan A ff5391c6ff1e

Subscribe to this mod's changes

novel-to-script-team AGENTS.md is an instructions file published in the GitHub repository Supreme-Ultimate/novel-to-script-team (161 stars, last pushed 4mo ago), licensed MIT. It adds 3,975 tokens to every session, about $0.0199 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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