humanize

An agent skill that audits prose for the tells of AI writing and rewrites them out, without flattening the author's voice. Runs in Claude Code, Codex, Cursor, Hermes Agent, Claude Desktop.

The reference entries rest on thirteen studies. The base rates come from the widest human-vs-AI gaps in StoryScope (2026), which measured 304 narrative and stylistic features over 61,575 stories. Reinhart et al. (2025) put participial modifiers at 5.3 times the human rate and nominalization at 2.1 times. Repeated phrasing turned out to be the strongest true signal of a text's source (Jakesch et al. 2023). Findings also expire: Herbold et al. (2023) saw lexical diversity reverse between model generations. humanize turns that work into an audit checklist plus a dependency-free scanner for the counts a model cannot eyeball. Every flag quotes the line it came from. One pattern organizes the whole checklist: AI converges on shared defaults while human writing disperses. Every cited number resolves in references/SOURCES.md.

Install

Requires Python 3.9+ on PATH for the scanner. No other dependencies. Commands were checked against each CLI's --help for this release; installs that fetch from GitHub (Codex, Hermes) are exercised at the acceptance steps recorded in docs/acceptance/.

Harness	Install	Verify	Invoke
Claude Code	/plugin marketplace add ccf/humanize then /plugin install humanize@humanize	claude plugin list	/humanize … or automatically
Codex CLI	codex plugin marketplace add ccf/humanize then codex plugin add humanize@humanize — or cp -R skills/humanize ~/.agents/skills/	codex debug prompt-input "hi" lists the skill	$humanize … or automatically
Cursor	cp -R skills/humanize ~/.cursor/skills/ (every project) or .cursor/skills/ (this project)	the skill appears in the / menu	/humanize … or automatically
Hermes Agent	hermes skills install ccf/humanize/humanize --category writing; in a running session, /reload-skills	hermes skills list	/humanize … or automatically
Any Agent-Skills harness	npx skills add ccf/humanize or cp -R skills/humanize ~/.agents/skills/	harness-specific	harness-specific
Claude Desktop (macOS, Windows)	Customize → Plugins → Add from repository ccf/humanize → install humanize → restart the app	listed under Customize → Plugins; /humanize:humanize in the picker	/ or + picker, or automatically, in chats and Cowork
claude.ai on the web or mobile, or without a linked repo	Customize → Skills → upload humanize-skill-<version>.zip from the latest release; "Code execution and file creation" must be on	listed under Customize → Skills	automatically, or the sidebar / menu

Notes:

• Codex reads <repo>/.agents/skills/ and ~/.agents/skills/ but not .claude/skills/, and caps the injected skills catalog at 2% of the context window. A long catalog drops skills.
• Cursor syncs only ~/.cursor/skills/ to Cloud Agents, and only with Sync Skills for Cloud Agents on (Settings → Agents). The Cursor marketplace is reviewed by hand and has no CLI.
• Hermes scans installed scripts (surface_scan.py is standard-library and passes) and runs the scanner on the host, so on a remote terminal backend (docker, modal, ssh) the scan step is skipped and the audit proceeds from reading alone. hermes plugins install also works on recent builds but installs the package disabled and read-only. Prefer hermes skills install. Installing from a raw SKILL.md URL fetches one file and is not supported.
• Claude Desktop picks up a plugin update only when version changes, and it needs a restart after installing or updating a plugin: until then the / menu can list a skill the app cannot yet invoke ("Unknown command: /humanize:humanize"). The zip is only for claude.ai without the Desktop app. In claude.ai chat the skill triggers by description. Picking it from the / menu passes no arguments.
• Word, PDF, PowerPoint inputs. humanize leaves extraction to the harness's document skills. In Claude Code that is Anthropic's document-skills plugin (/plugin marketplace add anthropics/skills, /plugin install document-skills@anthropic-agent-skills; its docx read path uses pandoc — brew install pandoc on macOS). Claude Desktop ships the same skills.

Use

Automatically. The skill activates whenever Claude drafts or edits prose. It checks its own output against the tell lists and returns the text.

Explicitly.

/humanize draft.md
/humanize "Great question! I'd be happy to help you navigate…"
/humanize draft.md --audit-only
/humanize story.md --fiction
/humanize report.docx          # extracted via the docx skill, rewrite returned as Markdown

Output: an audit table (at most ten tells, each with a quoted example and the measured base rate or scan metric), a one-line statement of the voice being preserved, the rewrite, before/after metrics, and a list of any additive choices you may want to reverse.

Example

Input (excerpt):

Great question! I'd be happy to help you navigate the complexities of the migration timeline. […] It's not just about moving the data; it's about transforming how we work. […] Ultimately, this migration is a testament to our commitment to excellence.

Audit:

#	Tell	Evidence	Base rate / metric
1	Validating opener	"Great question! I'd be happy to help"	—
2	AI wordlist	leveraging, seamless, robust, testament to (+6)	68/1k (human < 3)
3	Tricolon habit	"performance, scalability, and maintainability" (×3)	3 in 140 words
4	Not-X-but-Y	"not just about moving the data; it's about"	1
5	Summary closer	"Ultimately, this migration is a testament to"	fired
6	Uniform sentence length	cv 0.29	human 0.5–0.9

Voice: direct, peer-to-peer, mildly informal; a status update to a colleague.

Rewrite (excerpt):

Sarah — here's where the migration stands. The old system works but it's carrying a lot of debt, and we looked hard at performance and at how much it costs to maintain. Moving the data is the easy part. […]

Principles

• Disperse, don't converge. A tell is an unchosen default. The fix is a choice, not a new default.
• Preserve voice and meaning. Every fact and the author's register survive.
• Fix only what fired. Everything else stays as written.
• Removals over additions. Cutting an epilogue is safe; adding a joke is a choice, and the report says so.
• Numbers are evidence, not verdicts. This is a writing tool. It never claims text is undetectable or "certified human".
• Register and proficiency are not tells. Formal, plain-language, technical, and second-language prose share the measured AI profile. The plugin measures it and never infers authorship from it.

What's inside

skills/humanize/
  SKILL.md                     the procedure
  references/
    principles.md
    surface-tells.md           vocabulary, punctuation, shape, discourse moves
    style-tells.md             20 style features with StoryScope base rates
    narrative-tells.md         57 narrative features (fiction only), StoryScope base rates
    model-fingerprints.md      Claude / GPT / Gemini / DeepSeek / Kimi tendencies
    SOURCES.md                 citation registry (not loaded at runtime)
  scripts/surface_scan.py      stdlib-only metrics: burstiness and sentence tails, punctuation,
                               tricolons, not-but, wordlists, closers, repeated phrases,
                               participial tails, container nouns, nominalization hits,
                               disclaimer opener
data/                          StoryScope taxonomy + computed feature gaps
tools/gen_tell_scaffold.py     regenerate reference scaffolds from the data
tests/                         pytest; no network, no LLM calls

Development

uv sync
uv run pytest -q
claude plugin validate --strict .
uv run python skills/humanize/scripts/surface_scan.py --text some.txt

CI (.github/workflows/ci.yml) runs the same pre-commit hooks, pytest on Python 3.9 and 3.13, and claude plugin validate --strict on every pull request.

tests/fixtures/expected_tells.md is a manual checklist: run /humanize tests/fixtures/<file> --audit-only after editing the skill and compare.