本文へ移動
cccskills
無料GitHub で公開

human-ai

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.

インストール方法を見る

含まれるファイル(8)

  • SKILL.md7.2 KB
  • references/patterns-composition.md13.3 KB
  • references/patterns-content.md5.9 KB
  • references/patterns-english-specific.md8.0 KB
  • references/patterns-language.md10.7 KB
  • references/patterns-style.md5.5 KB
  • references/patterns-tone.md5.8 KB
  • references/presets.md10.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Audit, score, and compare repositories containing portable Agent Plugins against the official Agent Plugins specification. Use when asked to review a plugin repo, check plugin.json or mcp.json conformance, assess bundled skills and MCP servers, produce an evidence-cited 0–100 plugin scorecard, identify release blockers, or compare two agent plugins side by side.

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

Sub-skill de agent-ready-cloudflare: Implement A2A Agent Card

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

Sub-skill de agent-ready-cloudflare: Implement ACP Discovery Document

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

Sub-skill de agent-ready-cloudflare: Implement Agent Skills Discovery Index

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

Sub-skill de agent-ready-cloudflare: Implement AI Bot Rules in robots.txt

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

Sub-skill de agent-ready-cloudflare: Implement API Catalog

日本語の概要は準備中です。原文の説明を表示しています。

fabricioctelles/skills1072026年10月12日 更新

fabricioctelles のスキルをすべて見る

このスキルの問題を報告する