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sepia

Nanako0129 · Nanako0129/sepia

A writing skill that removes AI-sounding patterns, repairing narrative structure in fiction and applying venue-specific rules to professional documents.

De-AI writing skill for any Agent Skills-compatible agent (77+ via the Skills CLI), with native plugins for Claude Code, Codex, Grok Build, and Antigravity. Narrative-architecture repair for fiction, venue-matched rules for professional prose. Based on StoryScope (arXiv:2604.03136).

3k stars193License: MITUpdated 12 days ago0 opens

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What you can do with it

  • Rewrite AI-sounding release notes or PR replies so they read naturally
  • Review a short story draft and diagnose its AI tells
  • Polish a postmortem or technical article with minimal edits

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From the README

sepia

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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, Antigravity, and QwenPaw 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).

Table of Contents


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:

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

A 30-feature diagnosis rubric and per-model fingerprints across two layers apply when the writing or executing model is known:

Model familyNarrative layer (StoryScope)Sentence-level prose layer (Vendor prompting guides)
ClaudeMeasuredClaude Fable 5.1 and Mythos 5.1, Fable 5 and Mythos 5, Opus 5, Opus 4.8
GPTMeasuredGPT-5.6, GPT-6 Astra
GeminiMeasuredGemini 3 and 3.1
DeepSeekMeasuredConsulted (no guidance published)
KimiMeasuredConsulted (no guidance published)

Notice: Vendors that publish no prompt guidance are recorded as consulted, not guessed.

Professional prose fails differently, and the structure-level finding holds there too: a 2026 replication of StoryScope on 2,250 company blog posts against 11,250 AI mirrors separated them at 98.0 macro-F1 from structural features alone, with the AI shape described as tidy and self-announcing (SLOPSHAPE-2026 in the ledger, arXiv:2609.15369; a preprint whose features are LLM-scored; it tested detection of original and model-self-reworded posts, never human editing). 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:

DomainThe gist
Release notes / announcementsuser impact first, artifacts per claim, no marketing inflation
PR / issue repliesanswer first, cite file:line, no reflex praise, length ∝ stakes
Postmortemsblameless toward people, merciless toward mechanisms; timestamps, dead ends, owned action items
Tickets / work orderstitle = outcome, testable acceptance criteria, link don't repeat
Technical articlesopen at the problem, one real dead end, one committed opinion, numbers with conditions
Long-form journalism (features, investigations, data stories)lead and body in two registers, quotations keep their spoken texture, every number carries a comparison, no summary ending

Governing principle: 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. QwenPaw gets the /sepia router only, so the table below does not apply there:

OperationClaude CodeCodexGrok BuildAntigravityMeaning
write/sepia-write$sepia-write/sepia-write/sepia-writeCreate new prose
review/sepia-review$sepia-review/sepia-review/sepia-reviewDiagnose without editing
refactor/sepia-refactor$sepia-refactor/sepia-refactor/sepia-refactorMake minimal in-place edits
recreate/sepia-recreate$sepia-recreate/sepia-recreate/sepia-recreateRewrite from the source facts and intent
hemingway/sepia-hemingway$sepia-hemingway/sepia-hemingway/sepia-hemingwayWrite or refactor fiction with the built-in Hemingway voice applied

The general /sepia (Claude Code, Grok Build, Antigravity, and QwenPaw) or `$sep

View source on GitHub