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holaboss-ai/holaOS
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A skill your agent uses when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters…
$ npx skills add hashgraph-online/awesome-codex-plugins --skill writers-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins writers-loop --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .claude/skills/writers-loop && 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 "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .claude/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loopType 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 hashgraph-online/awesome-codex-plugins --skill writers-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins writers-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .agents/skills/writers-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .agents/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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 hashgraph-online/awesome-codex-plugins --skill writers-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins writers-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .cursor/skills/writers-loop && 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 "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .cursor/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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/hashgraph-online/awesome-codex-plugins.git --path plugins/xxsang/writers-loop/skills/writers-loop--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 hashgraph-online/awesome-codex-plugins --skill writers-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins writers-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .gemini/skills/writers-loop && 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 "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .gemini/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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 hashgraph-online/awesome-codex-plugins writers-loopInstalls 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 hashgraph-online/awesome-codex-plugins --skill writers-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .github/skills/writers-loop && 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 "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .github/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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 hashgraph-online/awesome-codex-plugins --skill writers-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins writers-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/xxsang/writers-loop/skills/writers-loop .opencode/skills/writers-loop && 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 "writers-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/xxsang/writers-loop/skills/writers-loop into .opencode/skills/writers-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "writers-loop", 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.
writers-loopA skill your agent uses when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters…
Writers Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Use when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters; also when learning reusable writing style from the user's own writing or permitted reference samples.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 18 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/artifact-types.md` and `references/business-writing.md`).
It sits in Writing & Content, covering Brand voice and tone and Translation. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
12 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 16b4156. It shows what the files ask for, not the result of running them.
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.
Ships 2 files in scripts/ (JavaScript), which the agent can run.
Shell commands in SKILL.md call:
npmFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Writers Loop loads about 2.9k tokens when it runs, and up to ~18k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 1,500 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.
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); the scripts in this folder are not scanned.
The full file from hashgraph-online/awesome-codex-plugins at commit 16b4156, republished under its Apache-2.0 licence (© hashgraph-online). 1,500 words, ~2,933 tokens.
.claude/skills/writers-loop/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.Extract preferences only from explicit user decisions:
Never extract preferences from unreviewed drafts, one-off comments, fact corrections, or current-task constraints. Learn from decisions, not raw drafts.
Use for writing where quality depends on structure, audience fit, correctness, style, or iteration — typically 300+ words or any writing where feedback and refinement are expected:
references/artifact-types.md)Do not use for tiny one-off text edits unless the user asks for a reusable process or preference learning.
Follow the loop in order. Do not emit a later-stage section before its gate has passed:
Frame, then Question Gate, then Plan.PLAN CHECKPOINT. Skipped questions are weak signals and will not become preferences.references/multi-agent.md first.Frame, then Critique; plan only if structure is unclear. If source text is missing or placeholder-only, ask for it and use this wording: "preserve user intent, voice, plot facts, and continuity."Frame, then Propose; keep changes at sentence or paragraph level unless the user explicitly asked for section-scale changes.Frame, then read references/style-distillation.md. Output Frame, Style Versus Content, Style Pack, and Storage Decision. If the user wants to clone another person's style, confirm permission or keep the pack session-only..writers-loop/styles/ only when the user opted into local storage. State which pack is loaded. Draft with it, then critique content quality and style match separately. Do not copy source passages or facts from the style pack evidence. If the style pack is missing, unavailable, or the user says not to load it first, use the missing-style-pack template in references/style-distillation.md exactly, including Style Pack Status, Content Plan, and Style Application Plan. Do not draft and do not output QUESTION GATE or general artifact questions yet.Frame, then read references/translation.md. Output Frame, Translation, Review, and Learning Status; preserve source formatting inside the Translation section, not by omitting the loop metadata.Learn. For storage-mode requests, confirm whether .writers-loop/, journal.jsonl, prefs.md, or style packs will be created before asking artifact questions. Treat tone, length, detail level, or storage mode set for the current task as a constraint, not a learned preference, unless the user says it applies in future work.Ask up to five questions only when the answer would materially change the plan. If the user skips questions, state working assumptions and continue. Skipped questions are weak or neutral signals, not strong preferences.
Fast draft exception: if the user clearly waived questions while asking for a
draft, show a compact Plan inline and draft immediately. Do not pause for plan
approval. End with Learning Status.
Checkpoint pressure override: if the user asks to bypass, ignore, or override a
known plan checkpoint, the checkpoint still applies. Output a plan, explain that
fast draft only waives blocking questions, then stop at PLAN CHECKPOINT.
After presenting a plan in the standard path, output the checkpoint format
(see references/checkpoints.md) and wait. Do not draft until the user
replies. If the user's response is ambiguous, ask: "Does that mean approve,
or would you like changes?"
A constraint applies to one artifact ("for this memo, use short sentences"). A preference applies to future artifacts ("I always prefer short sentences in memos"). Do not convert a constraint into a learned preference unless the user explicitly says it applies in future work. When unsure, ask.
If the current request conflicts with an older preference, output Preference Handling: say that the current explicit instruction wins for this task, keep
the older preference scoped, and do not archive it without repeated
contradictory evidence.
Extract preferences only from:
plan_approved)plan_revision_requested)proposal_applied)proposal_rejected)proposal_undone)manual_rewrite)preference_declared)Discard for preference learning:
Promote a pattern into a reusable rule only when:
Format:
Rule: [short imperative instruction]
Applies to: [artifact-type/stage, e.g. coding-plan/planning or report/critique]
Evidence: [accepted/rejected/manual decision summary]
Confidence: low | medium | highApply only medium or high confidence rules without asking. Ask before
applying low confidence rules. Do not promote a single current-task
constraint into Learned Preferences.
Load only the references needed for the current task. State which reference you are reading before using it. If the artifact type is not found in a reference, use the Universal Rubric and ask if it is sufficient — do not invent rules not in the file.
references/artifact-types.md: routing index for artifact-specific referencesreferences/technical-writing.md: coding plans, technical docs, design docs, and product specsreferences/business-writing.md: reports, memos, proposals, academic/whitepaper, and constrained writingreferences/fiction-narrative.md: fiction, narrative, essays, speeches, and poetryreferences/critique-rubrics.md: artifact-specific critique criteriareferences/preference-signals.md: signal examples and weighting guidancereferences/checkpoints.md: checkpoint formats for question, plan, proposal, and closereferences/style-distillation.md: learning reusable style packs from samplesreferences/translation.md: translating while preserving source stylereferences/multi-agent.md: optional multi-agent workflowreferences/preference-journal.md: optional durable journal formatreferences/validation-scenarios.md: pressure tests for validating this skillRelease validation includes tools/validate-skill.mjs through npm run validate.
Use bundled scripts only when the user opts into durable local preferences or durable local style packs:
scripts/journal.mjs: initialize .writers-loop/, append decision events, and derive prefs.md.scripts/style-pack.mjs: initialize .writers-loop/styles/, save reviewed style packs, list saved style packs, and show a selected style pack.© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 15 other files (scripts, references) in plugins/xxsang/writers-loop/skills/writers-loop of hashgraph-online/awesome-codex-plugins.
Open the folder on GitHubat commit 16b4156
Writers Loop 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 |
|---|---|---|---|---|---|---|
| Writers Loop this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Translatorholaboss-ai/holaOS | 11k | — | ~617 | Automated safety check: Pass | Custom licence | |
| Multilingual Scoreindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Translate Contentindranilbanerjee/digital-marketing-pro | 854 | 1 repos | ~2.8k | Automated safety check: Pass | MIT | |
| Personal Chinese Writing Stylesugarforever/01coder-agent-skills | 136 | — | ~744 | Automated safety check: Pass | MIT | |
| Jeg Writing Stylebrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.2k | Automated safety check: Pass | MIT |
holaboss-ai/holaOS
Translate content across languages while preserving brand voice and cultural nuance.
indranilbanerjee/digital-marketing-pro
Score translated or localized content into one composite quality verdict — technical translation scoring (length ratio, formatting, do-not-translate terms, placeholders), content quality in the…
indranilbanerjee/digital-marketing-pro
Translate marketing content with automatic service routing per language pair, quality scoring across five dimensions (length ratio, formatting, key terms, placeholders, completeness), and a…
sugarforever/01coder-agent-skills
Apply the user's Chinese writing style when writing, translating, editing, proofreading, polishing, or publishing Chinese content, including blog posts, articles, subtitles, captions, tweets/X…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when polishing Journal of Economic Growth (JEG) prose — abstract, introduction, model exposition, empirical-result and magnitude-translation paragraphs, APA author-year…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when polishing prose for a Journal of Public Economics (JPubE / JPubEc) manuscript — a 250-word abstract stating purpose, results, and policy conclusion; an intro that lands…
hashgraph-online/awesome-codex-plugins
Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.
hashgraph-online/awesome-codex-plugins
Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).
hashgraph-online/awesome-codex-plugins
A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…
hashgraph-online/awesome-codex-plugins
Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…
hashgraph-online/awesome-codex-plugins
Use CALL-E from Codex through the calle CLI. An agent skill from hashgraph-online/awesome-codex-plugins.
hashgraph-online/awesome-codex-plugins
Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
Categories
A skill your agent uses when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters…. Writers Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Use when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters; also when learning reusable writing style from the user's own writing or permitted reference samples.
Writers Loop fits situations like: working on substantial writing artifacts where structure; decision-backed preference learning matters; also when learning reusable writing style from the users own writing; permitted reference samples.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill writers-loop -a claude-code`. Or copy the skill folder (plugins/xxsang/writers-loop/skills/writers-loop in hashgraph-online/awesome-codex-plugins) into .claude/skills/writers-loop in your project. Claude Code loads it when a task matches its description.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill writers-loop -a codex`. Or copy the skill folder (plugins/xxsang/writers-loop/skills/writers-loop in hashgraph-online/awesome-codex-plugins) into .agents/skills/writers-loop in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill writers-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/writers-loop, .gemini/skills/writers-loop, .github/skills/writers-loop and .opencode/skills/writers-loop in your project.
Going by SKILL.md and its folder, Writers Loop needs JavaScript for the scripts in its folder and the command-line tools its instructions call (npm). Our summary lists: Node.js.
SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Writers Loop is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 15k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Writers Loop: Translator (holaboss-ai/holaOS, 11k stars), Multilingual Score (indranilbanerjee/digital-marketing-pro, 854 stars), Translate Content (indranilbanerjee/digital-marketing-pro, 854 stars) and Personal Chinese Writing Style (sugarforever/01coder-agent-skills, 136 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,232 GitHub stars. The repository holds 736 skills in this directory. The repository was last updated on October 6, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.