sepia README

The project's README from github.com/Nanako0129/sepia. As one markdown file: README.md.

sepia

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behavioral eval version consistency release license: MIT

De-AI writing at the layer that actually gives AI away. Fiction gets its narrative architecture repaired before anyone touches word choice; professional documents (release notes, PR replies, postmortems, tickets, technical articles) each get rules matched to their venue.

A portable Agent Skill: any agent that speaks the standard can load it, and the Skills CLI, which supports 77+ agents, installs it with one command. Claude Code, Codex, Grok Build, and Antigravity additionally get native plugin packaging. One canonical SKILL.md, no per-platform forks. Four operations: write, review (diagnose only), refactor (minimal edits), recreate (full rewrite).

Why another humanizer

Every popular humanizer edits word choice and syntax. StoryScope (Russell et al., 2026: 61,608 stories, human + 5 frontier LLMs) showed that a classifier using narrative-structure features alone detects AI fiction at 93.2% macro-F1. In the same study's LAMP-edited condition, where human editors had rewritten the surface style, detection dropped only from 95.5% to 93.9%. The tells that survive are architectural: themes explained by the narrator, single-track causally-tidy plots, emotions rendered only as bodily sensation, no real-world references, no reader, linear time, endings resolved by protagonist growth and acceptance.

sepia turns those measured gaps, together with the related studies digested in research/, into a three-pass writing and revision protocol for fiction:

Pass Layer Examples
1 Narrative architecture (fiction) stop explaining the theme, loosen the causal chain, back-load revelations, mix emotion modes, sparse character networks, name real things
2 Discourse flow de-template the paragraph-question sequence, fix the mid-story sag, vary rhythm and positions
3 Surface style the classic layer: clichés, syntax templates, vocabulary, register

Plus a 30-feature diagnosis rubric and per-model fingerprints in two layers: narrative tells measured by StoryScope (Claude, GPT, Gemini, DeepSeek, Kimi) and sentence-level tells taken from the vendors' own prompting guides (Claude Fable 5.1 and Mythos 5.1, Fable 5 and Mythos 5, Opus 5, Opus 4.8; GPT-5.6, GPT-6 Astra; Gemini 3 series), applied when the writing or executing model is known. Vendors that publish no such guidance are recorded as consulted, not guessed.

Professional prose fails differently. The studies digested in research/ point at filler that carries no information, hedging where a judgment was needed, chatbot leftovers, register that ignores the venue, and formatting that looks stamped out. Each document type gets a thin rule file on top of one shared checklist:

Domain The gist
Release notes / announcements user impact first, artifacts per claim, no marketing inflation
PR / issue replies answer first, cite file:line, no reflex praise, length ∝ stakes
Postmortems blameless toward people, merciless toward mechanisms; timestamps, dead ends, owned action items
Tickets / work orders title = outcome, testable acceptance criteria, link don't repeat
Technical articles open at the problem, one real dead end, one committed opinion, numbers with conditions

The governing principle throughout: calibrate to the human distribution, don't invert the AI one. Humans sit at moderate values; a story with every rule applied is a new fingerprint. The skill selects 3–5 moves per story and leaves slack.

Operation entries

The complete plugin package gives Claude Code, Codex, Grok Build, and Antigravity a general router plus five direct entries:

Operation Claude Code Codex Grok Build Antigravity Meaning
write /sepia-write $sepia-write /sepia-write /sepia-write Create new prose
review /sepia-review $sepia-review /sepia-review /sepia-review Diagnose without editing
refactor /sepia-refactor $sepia-refactor /sepia-refactor /sepia-refactor Make minimal in-place edits
recreate /sepia-recreate $sepia-recreate /sepia-recreate /sepia-recreate Rewrite from the source facts and intent
hemingway /sepia-hemingway $sepia-hemingway /sepia-hemingway /sepia-hemingway Write or refactor fiction with the built-in Hemingway voice applied

The general /sepia (Claude Code, Grok Build, and Antigravity) or $sepia (Codex) router remains available. The operation wrappers depend on their sibling canonical skill, so standalone wrapper installation is unsupported; install the complete plugin package. What was verified on each platform is stated under Install.

Experimental: composing with voice skills

Since v0.4.0, sepia defines an interface for stacking a voice or style skill on top of it — a minimalism method, a brand voice, a persona guide. It is opt-in: tell sepia the voice skill is in play, and it loads references/voice-skills.md over the normal route. No external voice is loaded unless you say so.

The contract in short: sepia's architecture decisions come first. The voice's moves are applied selectively (3–5 signature moves per piece, formula endings deliberately broken sometimes). Review reports the voice's known costs instead of fixing them away, while uniformity findings keep full strength: a voice does not excuse a metronome. On professional routes the venue still sets the register. Direct conflicts come back to you. The interface is grounded in one blind review experiment on a strict-minimalism specimen — a worked example, not measured evidence. One built-in profile ships under references/voices/ (Hemingway: iceberg omission for fiction, the Kansas City Star rules for professional prose, each move traced to its source). The built-in profile follows the same rule. On fiction, a review only reports when your text's recorded findings fit the Hemingway profile; it loads nothing. Asking for strong de-AI on a story counts as opting in, and sepia then says which profile it is applying and how to decline. /sepia-hemingway is the direct entry.

Sentence rhythm and Chinese calibration

The style pass checks the spread of sentence lengths, the one syntactic measure on which every study that measured it agrees (human text varies more within a passage, in English and in Chinese); mean sentence length, punctuation counts, and paragraph length are not treated as signals because the measured directions contradict each other. Chinese text loads references/languages/zh.md, a calibration built on the one measured Chinese corpus (HC3, 2023) with its limits stated in the file; evidence and numbers are in research/rhythm-syntax.md.

Install

Every command below is written for user scope — install once, use it in every project.

Any agent (Skills CLI, 77+ agents)

npx skills add Nanako0129/sepia -g     # -g = user scope; the default is project
npx skills update sepia -g             # update
npx skills remove sepia -g             # uninstall

Installs on every agent the Skills CLI supports — Cursor, Cline, Windsurf, Copilot, OpenCode, goose, and more. Pick your agents when prompted. Runtime behavior outside the four platforms below has not been exercised by us; the skill is plain markdown under the Agent Skills standard, so file an issue if your agent trips on it.

The four platforms below have native plugin installers, each exercised with a live install. Verified means the install completes and the sepia entries appear. Whether the entries then behave as documented has not been checked platform by platform.

Claude Code

# install
claude plugin marketplace add Nanako0129/sepia
claude plugin install sepia@sepia --scope user

# update
claude plugin marketplace update sepia
claude plugin update sepia

The in-session /plugin install dialog asks you to pick a scope — choose User there.

Codex

# install
codex plugin marketplace add Nanako0129/sepia
codex plugin add sepia@sepia

# update — refresh the marketplace snapshot, then re-add to pick up the new version
codex plugin marketplace upgrade sepia
codex plugin add sepia@sepia

Grok Build

# install
grok plugin install Nanako0129/sepia --trust

# update
grok plugin update

Grok also auto-discovers a Claude Code install of sepia if you have one; either route works.

Antigravity

# install directly from GitHub
agy plugin install https://github.com/Nanako0129/sepia

Project scope (alternative)

When one repo should pin its own copy, commit skills/sepia/ into that repo as .agents/skills/sepia (Codex + Antigravity) or .claude/skills/sepia (Claude Code).

Uninstall

Each tool uses its native command:

# Claude Code
claude plugin uninstall sepia@sepia --scope user

# Codex
codex plugin remove sepia@sepia

# Grok Build
grok plugin uninstall sepia

# Antigravity
agy plugin uninstall sepia

Layout

sepia/
├── plugin.json              # Antigravity packaging
├── skills/
│   ├── sepia/                # canonical skill (Agent Skills standard)
│   │   ├── SKILL.md          # routing, operations, calibration rules, guardrails
│   │   └── references/       # passes, rubric, fingerprints, domain rules, languages/zh.md, voice-skills (experimental)
│   ├── sepia-write/SKILL.md  # thin fixed-operation wrappers
│   ├── sepia-review/SKILL.md
│   ├── sepia-refactor/SKILL.md
│   ├── sepia-recreate/SKILL.md
│   └── sepia-hemingway/SKILL.md  # fiction write/refactor with the built-in voice
├── .claude-plugin/          # Claude Code packaging (plugin.json, marketplace.json)
├── .codex-plugin/           # Codex packaging
├── .agents/                 # Codex/Antigravity workspace-mode discovery + Antigravity workflow
└── research/                # digested evidence base with sources

Star History

Star History Chart

Sources

Full digests with links in research/. Primary: StoryScope (arXiv:2604.03136); LAMP (CHI 2025); Measuring AI Slop (arXiv:2509.19163); Reinhart et al. (PNAS 2025); Russell et al. (ACL 2025); NarraBench (arXiv:2510.09869); Echoes in AI (PNAS 2025); QUDsim (COLM 2025); Beguš (2024); Beyond Checkmate (EMNLP 2025); Nonaka & Perry (2025); Chakrabarty et al. (2026); Shan, Lee & Hao (2026); Rohrbacher et al. (2026).

Support

You can use sepia for free without an account. The research behind every rule is open. Ongoing costs are just maintainer time and two kinds of model quota: delegating literature surveys to research agents that read primary papers, and running live models to test rule changes on A/B stories and cross-platform end-to-end reviews before shipping. You can support the project on Patreon.

Support sepia on Patreon

License

MIT

sepia (Nanako0129/sepia)

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3.2K ·GitHub
这是什么东西?Sepia 是一个面向编程代理的去 AI 味写作技能:它在叙事架构层面修复有 AI 腔的文本——小说的故事结构,以及针对发布说明、PR 回复和事后复盘等文档、与文体匹配的规范。
它是一个独立应用,还是我的编程代理加载的东西?它不是一个应用:只有一个用纯 Markdown 编写的标准 SKILL.md 文件,任何兼容的代理都能加载,没有按平台分叉的版本。Claude Code、Codex、Grok Build 和 Antigravity 额外提供原生插件打包。
哪些代理能运行它——我需要特定的某个吗?Skills CLI 支持的 77+ 个代理都可以——包括 Cursor、Cline、Windsurf、Copilot、OpenCode、goose 等等。Claude Code、Codex、Grok Build 和 Antigravity 有原生的 /sepia-* 条目;运行时没有任何依赖。
它在各个安装平台上表现都一样吗?除四个原生平台外,其他平台的运行时行为未经实际测试——在那四个平台上,“已验证”也只是指安装能完成、条目会出现。独立的包装安装方式不受支持;请安装完整的插件包。
sepia 对一段文本究竟能做什么?四种操作:write(写新文本)、review(只诊断不修改)、refactor(最小化的原地修改),以及 recreate(根据原始事实和意图完全重写)。每种操作都有直接入口,比如 /sepia-write,另有 /sepia-hemingway 可用内置的海明威文风写作。
它和其他“去 AI 味”工具有什么不同?流行的去 AI 味工具只改措辞,但 StoryScope 研究发现,仅凭叙事结构特征检测 AI 小说就能达到 93.2% 的 macro-F1,而表面改写只能把检测率从 95.5% 降到 93.9%。Sepia 先修复架构层面的破绽——比如替主题发声的叙述者、过于工整的单线情节——表面文风只是三遍处理中的最后一遍。
我能在它之上叠加自己的写作文风或人设吗?可以,从 v0.4.0 起这是可选功能:告诉 sepia 你有一个文风技能在用,它就会在正常流程之上加载那个文风。架构决策优先,文风在每篇作品中只贡献 3-5 个标志性手法,技能还内置了一个海明威文风配置。
它能处理中文文本吗?可以。中文会加载一套专门的校准文件(references/languages/zh.md),它基于 HC3 语料库构建,相关局限在该文件中已说明。节奏检查依赖句长分布——这是研究中唯一公认在人类与 AI 文本之间存在差异的指标,英语和中文都是如此。
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