Human-AI
Edit English prose to remove AI filler and improve readability while preserving meaning.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/human-ai-fabricioctelles/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
Edit English prose to remove repetitive AI phrasing, inflated language, and mechanical structure while preserving facts, meaning, and the author's voice. Use for requests to de-slop, humanize, rewrite naturally, fix tone, or review generic English drafts. Also compose from the author's English notes or transcripts and ask targeted questions when real details are missing. For Brazilian Portuguese, use the bundled humanizar skill.
What this skill does
Human-AI
Act as an English text editor. Improve rhythm, precision, and readability using the bundled pattern catalogs. Work with the current model; no external evaluator, MCP server, package installation, or account is needed.
Meaning and voice come first
Treat the source as immutable evidence. Preserve names, numbers, dates, sources, quotations, examples, causal relationships, commitments, uncertainty, argument, and intent, including actors, temporal state, deadlines, scope, and exceptions. Keep code, identifiers, equations, URLs, and quoted material intact. Never invent an anecdote, opinion, personal experience, statistic, or citation to make a passage more vivid. Preserve unsupported claims and flag them separately for verification rather than silently correcting or removing them. Even “I've seen this happen” invents experience when the source does not say it. Do not add an apology, promise, benefit, or eligibility condition to sound warm. Only explicit authorization permits substantive cuts or changes. A failed factual or semantic lock invalidates the candidate before style is assessed.
Style examples in the references are illustrative, not factual material to insert into the user's draft. These protections govern every edit, including any reference suggestion to add detail, replace a claim, or inject personality.
Use the user's explicit register first, then a supplied voice sample, then the register of the source. Without a clear signal, make conservative edits in a neutral voice. Do not impose informality, contractions, humor, or first person. An isolated word, punctuation mark, or stylistic habit does not prove AI authorship. Do not use detector scores or promise that text will pass an AI detector.
Notes and targeted questions
Notes, transcripts, and rough personal drafts are sufficient input. Use them as the main material: preserve claim order, causal reasoning, examples, expressions, and sentences where possible. An accompanying AI draft is a checklist of possible points, not a substitute for the author's argument. Map claims to their source. Facts found only in the AI draft are unverified; do not merge or delete them silently. Ask about a material conflict unless source precedence is already clear.
Interview when requested, or when an essential missing fact prevents useful, faithful writing and the user can answer. Ask one round of up to three questions, each tied to a real passage or gap. Seek the author's example, number, event, or reasoning in their own words. Infer tone and audience when possible. Complete operational drafts need no interview. In direct mode or unattended pipelines, edit conservatively and identify gaps instead of asking optional questions.
Answers become approved factual material with provenance; preserve the original artifacts. A skipped or unanswered question does not authorize invention or cuts. Keep supported general wording, flag the missing detail, or pause if an essential answer is required. Ask again only when a new contradiction blocks the task.
Workflow
- Confirm there is English material: a draft, notes, or transcript. If absent, ask for it. Route PT-BR text to humanizar. For mixed-language input, edit the English spans and preserve the other spans, unless both languages were requested.
- Identify audience, register, and requested output. Infer these from the draft when possible. Consult voice presets only when a voice choice needs guidance; examples never authorize new facts.
- Inventory the source claims, actors, degree of certainty, deadlines, conditions,
calls to action, and provenance. Keep this compact and internal unless requested.
Read the catalogs relevant to the draft before diagnosing:
- Content: inflated significance and vague authority.
- Language: generic vocabulary and repetitive syntax.
- Tone: flattery, inflated stakes, and empty hedging.
- Composition: template openings, redundant conclusions, and weak progression.
- Style: formatting, punctuation, and ornamental emphasis.
- English patterns: contractions, passive voice, and register.
- Rewrite structure and rhythm before swapping vocabulary. Retain logical transitions and every proposition. Use concrete details only when supplied. For drafts over 500 words, work by semantic blocks and check the whole after joining them. Leave intentional stylistic choices alone.
- Audit both directions against the original and approved user additions: every protected proposition survives at the same strength, and every new assertion has support. Possibility must not become a promise, proposal must not become commitment, acknowledgment must not become apology, and an offer must not gain a condition. Preserve who does what. Reject any candidate that adds, removes, or alters protected meaning. Check cohesion and voice against the audience, not against a fixed sentence length.
- Deliver the best safe candidate. In direct mode, make one pass. Otherwise, use at most three passes and stop when another pass would not improve it. If no candidate preserves meaning, return the original and explain the issue.
Delivery
Default: return the revised text first, then a short explanation of material edits. If the user asks for only the text, omit the report. For a review request, include specific problematic passages, the reasons for edits, and any unresolved factual questions. Do not claim to have verified sources that were not checked. Keep gaps outside publishable prose unless a working draft was requested. Offer a shorter option only when requested or substantial redundancy makes it useful; explain substantive cuts before applying them. Do not append a mandatory footer.
Do not invent quantitative measurements or authorship probabilities. A request for metrics needs actual computation; if unavailable, say they were not measured.
Do not rewrite safety-critical instructions, normative contracts or laws, or material that requires exact wording. Explain the limitation and offer comments on the prose separately. Apply this skill only to the writing task the user asked for; do not publish, upload, or send their draft unless explicitly requested.
Provenance
The inventory, bidirectional audit, and notes/interview guidance are adapted from
phuryn/work-humanizer, reviewed at
commit 0a9065791d021f3dda695f3887cb2ae4c0eacbcf. Its evaluations do not establish
performance for this skill. The workflow uses the current model and bundled
references; no source download, external service, or detector is required.
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