Thesis Creator
Stars-OC/thesis-creator
Walks Chinese undergraduates through writing a graduation thesis from topic to Word export, with text-similarity reduction and AI-text rate rewriting and checks.
Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre.
Install Humanize English
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-english --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/writing/humanize-english .claude/skills/humanize-english && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .claude/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-englishType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-english --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/writing/humanize-english .agents/skills/humanize-english && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .agents/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-english --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/writing/humanize-english .cursor/skills/humanize-english && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .cursor/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/AnastasiyaW/codex-claude-code-config.git --path skills/writing/humanize-english--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-english --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/writing/humanize-english .gemini/skills/humanize-english && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .gemini/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-englishInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/writing/humanize-english .github/skills/humanize-english && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .github/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config humanize-english --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/writing/humanize-english .opencode/skills/humanize-english && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "humanize-english" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/writing/humanize-english into .opencode/skills/humanize-english/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-english", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
humanize-english- GitHub stars
- 154
- Token cost
- ~1.8k tokens
- SKILL.md length
- 897 words
- Files
- 1
- Skills in repo
- 50
- Repo updated
- First seen
- Licence
- MIT
At a glance
Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre.
- Works in 6 steps: Identify the reader's task, genre,… → Remove empty intensifiers and duplicated… → Clarify who acts, on what, under which… → …
- : humanize this text
- SKILL.md covers Facts Are Not Style Material, Match the Genre, Editing Procedure and Examples: Same Facts, Clearer…, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Humanize English is an agent skill from AnastasiyaW/codex-claude-code-config. Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre. Use when: humanize this text, remove AI-style filler, improve English prose, or edit an English article before publication. Not an authorship detector or a promise to bypass one. For Russian use humanize-russian; for thesis/evidence and structure use article-structure-review.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Writing & Content, covering Humanizing AI text, Essays and academic help and Citation management. The repository describes itself as: Claude Code, Codex, and multi-agent configuration system: principles, hooks, skills, and workflow patterns for AI-assisted development. The licence is MIT.
When your agent uses it
- : humanize this text
- Remove AI-style filler
- Improve English prose
- Edit an English article before publication
Example prompts
- “/humanize-english”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Identify the reader's task, genre, source material and protected facts from
- Remove empty intensifiers and duplicated ideas. Use direct verbs when meaning
- Clarify who acts, on what, under which conditions and with what result.
- Fix awkward rhythm where it hinders reading. Do not maximize variation,
- Compare input and output for semantic changes. Check quantities with their
- Return the edited text and any necessary factual caveat. Once the edit is
What it can do on your machine
Read from SKILL.md and the folder at commit 67709af. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
arxiv.orgdevelopers.google.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Humanize English loads about 1.8k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 897 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from AnastasiyaW/codex-claude-code-config at commit 67709af, republished under its MIT licence (© AnastasiyaW). 897 words, ~1,816 tokens.
Download SKILL.mdSave it as
.claude/skills/humanize-english/SKILL.md (or your agent's skills folder).- name
- humanize-english
- description
- Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre. Use when: humanize this text, remove AI-style filler, improve English prose, or edit an English article before publication. Not an authorship detector or a promise to bypass one. For Russian use humanize-russian; for thesis/evidence and structure use article-structure-review.
- metadata.version
- 2.0.0
- metadata.reviewed
- 2026-09-06
Clear, Natural English Editing
Improve the reader's understanding, not a detector score. A good reference can have repeated terminology, regular tables, definitions and no anecdote. Keep the user's intended voice and the destination's format.
Facts Are Not Style Material
- Preserve supplied numbers, units, dates, versions, names, citations, negation, uncertainty and claim scope. Do not silently update a historical date.
- Never invent a count, quote, interview, personal experience, experiment, failure, comparison or source to make prose more vivid.
- Add specificity only when the supporting evidence supplies it. If no measurement exists, retain uncertainty or remove an unsupported claim. An unsupplied number is not an improvement over a vague quantity.
- Label illustrative scenarios as hypothetical. Do not present them as a real case study or treat their invented values as proof of a product claim.
- Preserve identifiers, executable code and technical obligations. Words such as may, must, can and will are not interchangeable style alternatives.
- Reuse provided facts without asking the user to repeat them. Research a material factual gap when research is in scope; otherwise identify the gap without manufacturing an answer or blocking supported edits.
Match the Genre
| Genre | Useful editing | Avoid forcing |
|---|---|---|
| technical reference | exact terms, clear conditions, scannable structure | slang, story openings, rhetorical questions, sales CTA |
| explanation/tutorial | prerequisites and action/result sequence | an untested command described as verified |
| analysis | separate observation, inference and limits | stronger causal claims than the evidence supports |
| personal narrative | the author's supplied experiences and voice | invented first-person testimony |
| marketing | a supported benefit and relevant next action | fabricated testimonials, percentages or guarantees |
Contractions, fragments, humour, analogies and direct address are options, not quotas. Use them when they fit the audience and improve comprehension. Parallel lists and consistent terminology can be desirable in documentation.
Editing Procedure
- Identify the reader's task, genre, source material and protected facts from the existing request and draft. Do not add an unnecessary intake questionnaire.
- Remove empty intensifiers and duplicated ideas. Use direct verbs when meaning is preserved; keep connectors that express real causality or contrast.
- Clarify who acts, on what, under which conditions and with what result. Do not supply a result that the source does not establish.
- Fix awkward rhythm where it hinders reading. Do not maximize variation, enforce a paragraph pattern or replace terms to appear less predictable.
- Compare input and output for semantic changes. Check quantities with their units, denominator, time frame and uncertainty, not just the numeral.
- Return the edited text and any necessary factual caveat. Once the edit is sufficient, continue the remaining requested publication workflow rather than starting another stylistic pass automatically.
Examples: Same Facts, Clearer Prose
| Supplied text | Faithful edit |
|---|---|
| In order to load the file, the user must select Open. | To load the file, select Open. |
| The tool may reduce processing time; no benchmark is available. | The tool may save processing time, but no benchmark is available. |
| Some testers reported failures. The sample size was not recorded. | Some testers reported failures; the sample size was not recorded. |
| On 2026-09-01, 12 of 40 runs failed with version 2.1. | With version 2.1, 12 of 40 runs failed on 2026-09-01. |
These are editing fixtures, not results from a deployed product. Unknown sample size stays unknown; a date, denominator and version do not disappear for fluency.
Show full SKILL.md (353 more words)Show less
Verification
- Every changed factual assertion still maps to the supplied material or a source actually checked for this task.
- Conditions, uncertainty, negatives, numbers, units, dates, versions and code are preserved unless an evidence-backed factual correction was requested.
- The result helps its intended reader without an unrequested genre change.
- No invented testimony or detector-evasion claim was added.
A no-change verdict is valid for an already clear passage. Do not add numbers, questions, opinions, deliberate errors or fake admissions to satisfy a score.
Gotchas
- Detector score as evidence: it establishes neither authorship nor factual accuracy. Do not promise an undetectable edit.
- Replacing every vague quantity: guessing a plausible percentage fabricates evidence when the sample size is unknown.
- Forced informality: slang can make a reference harder to understand, particularly for readers using English as an additional language.
- Synonym churn: repeating a technical term is safer than creating a false distinction through alternate names.
- Example contamination: a skill example is not an event that happened to the user or author.
Troubleshooting
| Symptom | Check | Correction |
|---|---|---|
| polished but unsupported claim | source scope and conditions | restore supported meaning or remove the claim |
| bureaucratic phrasing | action and actor | use a direct sentence without changing obligations |
| repetitive text | repeated meaning versus necessary terms | cut redundancy, keep precise terminology |
| reference sounds like an advertisement | requested genre | remove promotion and invented narrative |
| detector flags the passage | actual writing and detector limitations | repair evidenced defects, not a guessed authorship score |
Sources and Maintenance
Reviewed 2026-09-06. Owner: the existing writing-skill maintainers. Change through canonical Git, focused before/after fixtures, independent review and the supported installer; retain the prior revision and installation backup for rollback. Refresh sources when guidance changes or a factual/genre regression is observed, not by automatically rewriting working prose on a schedule.
- Developer documentation voice and tone, updated 2026-05-27: clarity and audience matter more than forced informality.
- GPT detectors are biased against non-native English writers, revised 2023-07-10: limitations of the evaluated detectors, not a test of every current detector or a guarantee about any individual passage.
- Excess vocabulary in biomedical publications, revised 2025-07-03: corpus-level biomedical analysis, not an individual-author test or a prescriptive word blacklist.
© AnastasiyaW, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/writing/humanize-english of AnastasiyaW/codex-claude-code-config.
Open the folder on GitHubat commit 67709af
Compare with similar skills
Humanize English next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Humanize English this skillAnastasiyaW/codex-claude-code-config | 154 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Thesis CreatorStars-OC/thesis-creator | 230 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Hlr Writing Stylebrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Academic HumanizerYila-AI/awesome-research-skills | 133 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Audit AI Writingjxnl/personal-monorepo-template | 563 | — | ~887 | Automated safety check: Pass | None | |
| AI Antislopagent-skills-hub/agent-skills-hub | 112 | — | ~1.9k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Humanize English
What does Humanize English do?
Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre. Humanize English is an agent skill from AnastasiyaW/codex-claude-code-config. Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre.
When should I use Humanize English?
Humanize English fits situations like: : humanize this text; remove AI-style filler; improve English prose; edit an English article before publication.
How do I install Humanize English in Claude Code?
Run `npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a claude-code`. Or copy the skill folder (skills/writing/humanize-english in AnastasiyaW/codex-claude-code-config) into .claude/skills/humanize-english in your project. Claude Code loads it when a task matches its description.
How do I install Humanize English in Codex?
Run `npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a codex`. Or copy the skill folder (skills/writing/humanize-english in AnastasiyaW/codex-claude-code-config) into .agents/skills/humanize-english in your project. Codex loads it when a task matches its description.
Can I use Humanize English in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AnastasiyaW/codex-claude-code-config --skill humanize-english -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/humanize-english, .gemini/skills/humanize-english, .github/skills/humanize-english and .opencode/skills/humanize-english in your project.
What does Humanize English need to run?
SKILL.md names no scripts, command-line tools or credentials: Humanize English is instructions for the agent only.
Does Humanize English access the network?
SKILL.md names 2 domains. As links in the text: arxiv.org and developers.google.com. This is read from the text; nothing was executed.
Is Humanize English safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Humanize English use?
Humanize English is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Humanize English use?
About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Humanize English?
Skills that share tags, products or a category with Humanize English: Thesis Creator (Stars-OC/thesis-creator, 230 stars), Hlr Writing Style (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars), Academic Humanizer (Yila-AI/awesome-research-skills, 133 stars) and Audit AI Writing (jxnl/personal-monorepo-template, 563 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Humanize English?
AnastasiyaW (a GitHub user) maintains it in AnastasiyaW/codex-claude-code-config, which has 154 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on October 9, 2026.
Source: AnastasiyaW/codex-claude-code-config on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.