sepia
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, install-verified on all four. 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, and that editing the surface style away barely moves it (95.5% → 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 eleven 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, Fable 5, Opus 5, Opus 4.8; GPT-5.6; 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 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 four direct operation 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 |
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. This table documents package syntax; installed UI and runtime behavior were not exercised as part of this change.
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. Nothing is loaded, and no aesthetic is ever injected, unless you say so.
The contract in short: sepia's architecture decisions come first, and 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, and 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.
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; runtime behavior is as noted above.
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, voice-skills (experimental)
│ ├── sepia-write/SKILL.md # thin fixed-operation wrappers
│ ├── sepia-review/SKILL.md
│ ├── sepia-refactor/SKILL.md
│ └── sepia-recreate/SKILL.md
├── .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
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).
License
MIT
