[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71JPAXMKQ1MMYRN588K5DWB":3,"skill-same:01M71JPAXMKQ1MMYRN588K5DWB":85},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":28,"publishedAt":48,"linkOnly":49,"markdownContent":50,"markdownBody":51,"frontMatter":52,"refName":45,"commitSha":65,"skillDirectory":5,"forksCount":14,"repositoryHtmlUrl":66,"repositoryHomepageUrl":6,"ownerHtmlUrl":67,"ownerBlogUrl":68,"ownerDescription":69,"updatedAt":70,"install":71,"resources":84},"01M71JPAXMKQ1MMYRN588K5DWB","unslop",null,"Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing","agency-black\u002FSkills","agency-black","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F234862658?v=4","01M6HWVFPNGNR5N2CX9ECSAD57","agencia.black","01M719WF77BF3HN0N9FK1APEFY",0,"MIT","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Funslop\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[5,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"safe","github","codex","post","antigravity","codex-cli","publishing","license","gemini","patterns","2026","cli","text","code","writing","generated","main","processing","community","2026-11-10 10:12:30",false,"---\nname: unslop\ndescription: \"Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing\"\ncategory: writing\nrisk: safe\nsource: community\nsource_repo: MohamedAbdallah-14\u002Funslop\nsource_type: community\ndate_added: \"2026-04-25\"\nauthor: MohamedAbdallah-14\ntags: [writing, content-quality, ai-writing, text-processing, cli, publishing]\ntools: [claude-code, cursor, gemini-cli, codex-cli, antigravity]\nlicense: \"MIT\"\nlicense_source: \"https:\u002F\u002Fgithub.com\u002FMohamedAbdallah-14\u002Funslop\u002Fblob\u002Fmain\u002FLICENSE\"\n---\n\n# unslop — Strip AI Writing Patterns via CLI\n\n## Overview\n\nunslop is a CLI tool that post-processes text to remove AI writing patterns programmatically. Unlike skills that ask the agent to avoid AI-isms, unslop runs as a deterministic pipeline step: pipe text in, get clean text out. Use it as a final pass before committing docs, publishing posts, or sending any AI-generated content to production.\n\nThe `--deterministic` flag makes output reproducible — same input always produces same output. The `--stdin` flag reads from stdin, enabling shell pipeline composition.\n\n## When to Use This Skill\n\n- When you have AI-generated text ready to publish and want a final cleanup pass\n- When working in a shell pipeline where text quality needs to be enforced automatically\n- When writing commit hooks or CI steps that validate content before it ships\n- When you need reproducible text normalization across multiple runs\n\n## Setup\n\nInstall once:\n\n```bash\npipx install unslop\n# or\nuv tool install unslop\n```\n\nVerify:\n\n```bash\nunslop --version\n```\n\n## How It Works\n\n### Step 1: Pipe Text Through unslop\n\nStandard cleanup (may vary slightly between runs):\n\n```bash\necho \"This leverages cutting-edge AI to deliver robust solutions.\" | unslop --stdin\n```\n\nDeterministic cleanup (same input → same output every run):\n\n```bash\necho \"This leverages cutting-edge AI to deliver robust solutions.\" | unslop --stdin --deterministic\n```\n\n### Step 2: Use in Shell Pipelines\n\nPipe the output of any command through unslop:\n\n```bash\ncat draft.md | unslop --stdin --deterministic > clean.md\n```\n\nOr chain with other tools:\n\n```bash\ncat draft.md | unslop --stdin --deterministic | pbcopy   # macOS: copy clean text to clipboard\n```\n\n### Step 3: Integrate into Commit Hooks or CI\n\nAdd to a pre-commit hook or CI step to enforce quality gates on any generated content before it ships:\n\n```bash\n# In .git\u002Fhooks\u002Fpre-commit or a CI script\nCONTENT=$(cat docs\u002Fchangelog.md)\nCLEANED=$(echo \"$CONTENT\" | unslop --stdin --deterministic)\nif [ \"$CONTENT\" != \"$CLEANED\" ]; then\n  echo \"Changelog contains AI writing patterns. Run: cat docs\u002Fchangelog.md | unslop --stdin --deterministic > docs\u002Fchangelog.md\"\n  exit 1\nfi\n```\n\n## Examples\n\n### Example 1: Clean a Draft Document\n\n```bash\ncat blog-post-draft.md | unslop --stdin --deterministic > blog-post-final.md\n```\n\n### Example 2: Inline Cleanup During Writing\n\n```bash\n# Write content, pipe through unslop, write result back\ncat README.md | unslop --stdin > README.clean.md && mv README.clean.md README.md\n```\n\n### Example 3: Validate Before Submitting a PR\n\n```bash\n# Check if any generated docs need cleanup\nfor f in docs\u002F*.md; do\n  ORIGINAL=$(cat \"$f\")\n  CLEANED=$(echo \"$ORIGINAL\" | unslop --stdin --deterministic)\n  [ \"$ORIGINAL\" != \"$CLEANED\" ] && echo \"Needs cleanup: $f\"\ndone\n```\n\n## Best Practices\n\n- ✅ Use `--deterministic` in CI and automation to ensure reproducible output\n- ✅ Run on the final draft, not intermediate iterations\n- ✅ Combine with the `avoid-ai-writing` skill for both generation-time guidance and post-processing\n- ❌ Don't run on code files — unslop targets prose, not source code\n- ❌ Don't skip review after unslop: automated cleanup can occasionally change meaning; read the output\n\n## Limitations\n\n- Processes prose only — not code, JSON, or structured data\n- Does not catch factual errors or substantive writing issues\n- Some replacements may not fit every context; review the output before publishing\n- Requires Python tooling such as `pipx` or `uv` for standalone CLI installation\n\n## Security & Safety Notes\n\n- unslop reads from stdin and writes to stdout — no file system side effects by default\n- `--deterministic` mode is local and does not make LLM API calls\n- Default LLM mode may use `ANTHROPIC_API_KEY` or the Claude CLI; use `--deterministic` for sensitive local files and CI gates\n- Safe to run in CI pipelines and commit hooks when pinned to deterministic mode\n","# unslop — Strip AI Writing Patterns via CLI\n\n## Overview\n\nunslop is a CLI tool that post-processes text to remove AI writing patterns programmatically. Unlike skills that ask the agent to avoid AI-isms, unslop runs as a deterministic pipeline step: pipe text in, get clean text out. Use it as a final pass before committing docs, publishing posts, or sending any AI-generated content to production.\n\nThe `--deterministic` flag makes output reproducible — same input always produces same output. The `--stdin` flag reads from stdin, enabling shell pipeline composition.\n\n## When to Use This Skill\n\n- When you have AI-generated text ready to publish and want a final cleanup pass\n- When working in a shell pipeline where text quality needs to be enforced automatically\n- When writing commit hooks or CI steps that validate content before it ships\n- When you need reproducible text normalization across multiple runs\n\n## Setup\n\nInstall once:\n\n```bash\npipx install unslop\n# or\nuv tool install unslop\n```\n\nVerify:\n\n```bash\nunslop --version\n```\n\n## How It Works\n\n### Step 1: Pipe Text Through unslop\n\nStandard cleanup (may vary slightly between runs):\n\n```bash\necho \"This leverages cutting-edge AI to deliver robust solutions.\" | unslop --stdin\n```\n\nDeterministic cleanup (same input → same output every run):\n\n```bash\necho \"This leverages cutting-edge AI to deliver robust solutions.\" | unslop --stdin --deterministic\n```\n\n### Step 2: Use in Shell Pipelines\n\nPipe the output of any command through unslop:\n\n```bash\ncat draft.md | unslop --stdin --deterministic > clean.md\n```\n\nOr chain with other tools:\n\n```bash\ncat draft.md | unslop --stdin --deterministic | pbcopy   # macOS: copy clean text to clipboard\n```\n\n### Step 3: Integrate into Commit Hooks or CI\n\nAdd to a pre-commit hook or CI step to enforce quality gates on any generated content before it ships:\n\n```bash\n# In .git\u002Fhooks\u002Fpre-commit or a CI script\nCONTENT=$(cat docs\u002Fchangelog.md)\nCLEANED=$(echo \"$CONTENT\" | unslop --stdin --deterministic)\nif [ \"$CONTENT\" != \"$CLEANED\" ]; then\n  echo \"Changelog contains AI writing patterns. Run: cat docs\u002Fchangelog.md | unslop --stdin --deterministic > docs\u002Fchangelog.md\"\n  exit 1\nfi\n```\n\n## Examples\n\n### Example 1: Clean a Draft Document\n\n```bash\ncat blog-post-draft.md | unslop --stdin --deterministic > blog-post-final.md\n```\n\n### Example 2: Inline Cleanup During Writing\n\n```bash\n# Write content, pipe through unslop, write result back\ncat README.md | unslop --stdin > README.clean.md && mv README.clean.md README.md\n```\n\n### Example 3: Validate Before Submitting a PR\n\n```bash\n# Check if any generated docs need cleanup\nfor f in docs\u002F*.md; do\n  ORIGINAL=$(cat \"$f\")\n  CLEANED=$(echo \"$ORIGINAL\" | unslop --stdin --deterministic)\n  [ \"$ORIGINAL\" != \"$CLEANED\" ] && echo \"Needs cleanup: $f\"\ndone\n```\n\n## Best Practices\n\n- ✅ Use `--deterministic` in CI and automation to ensure reproducible output\n- ✅ Run on the final draft, not intermediate iterations\n- ✅ Combine with the `avoid-ai-writing` skill for both generation-time guidance and post-processing\n- ❌ Don't run on code files — unslop targets prose, not source code\n- ❌ Don't skip review after unslop: automated cleanup can occasionally change meaning; read the output\n\n## Limitations\n\n- Processes prose only — not code, JSON, or structured data\n- Does not catch factual errors or substantive writing issues\n- Some replacements may not fit every context; review the output before publishing\n- Requires Python tooling such as `pipx` or `uv` for standalone CLI installation\n\n## Security & Safety Notes\n\n- unslop reads from stdin and writes to stdout — no file system side effects by default\n- `--deterministic` mode is local and does not make LLM API calls\n- Default LLM mode may use `ANTHROPIC_API_KEY` or the Claude CLI; use `--deterministic` for sensitive local files and CI gates\n- Safe to run in CI pipelines and commit hooks when pinned to deterministic mode\n",{"name":5,"risk":29,"tags":53,"tools":57,"author":61,"source":47,"license":15,"category":43,"date_added":62,"description":7,"source_repo":63,"source_type":47,"license_source":64},[43,54,55,56,40,35],"content-quality","ai-writing","text-processing",[58,59,60,34,33],"claude-code","cursor","gemini-cli","MohamedAbdallah-14","2026-04-25","MohamedAbdallah-14\u002Funslop","https:\u002F\u002Fgithub.com\u002FMohamedAbdallah-14\u002Funslop\u002Fblob\u002Fmain\u002FLICENSE","681496e0662f4c45c4758fae9d4510ae87311bf2","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills","https:\u002F\u002Fgithub.com\u002Fagency-black","http:\u002F\u002Fwww.dogma.black","Las grandes ideas merecen una ejecución impecable. Construimos plataformas web, aplicaciones y ecosistemas digitales completos. 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Compressed arrays, parallel I\u002FO, S3\u002FGCS via fsspec, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fzarr-python\u002FSKILL.md",[],[93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112],"zarr python","python","zarr","arrays","Cloud Storage","remote","workflows","scientific","read","write","edit","parallel","dask","for","s3fs","use","numpy","s3","scientific computing","scale",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":117,"sourceHtmlUrl":118,"categories":119,"keywords":123,"publishedAt":48},"01M71JYXC5VAEJT8KXN5GRK32S","xvary-stock-research","Thesis-driven equity analysis from public SEC EDGAR and market data; \u002Fanalyze, \u002Fscore, \u002Fcompare workflows with bundled Python tools (Claude Code, Cursor, Codex).","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FSKILL.md",[120],{"categoryNo":121,"categoryName":122,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",[124,125,126,127,128,47,129,94,130,99,131,42,132,133,134,135,136,31,59,39],"xvary","stock","research","xvary stock research","sec edgar","equity","thesis","analysis","Market","compare","market data","analyze","with",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":141,"licenseFileUrl":142,"sourceHtmlUrl":143,"categories":144,"keywords":151,"publishedAt":48},"01M71JVSDPDQ5040YBN6J1ASKY","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FSKILL.md",[145,148],{"categoryNo":146,"categoryName":147,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[152,153,154,106,155,156,157,158,159,160,161,136,162,163,164,165,166],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","playwright","web","behavior","ui","screenshots",{"skillNo":168,"name":169,"nameZh":6,"description":170,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":141,"licenseFileUrl":171,"sourceHtmlUrl":172,"categories":173,"keywords":175,"publishedAt":48},"01M71JV64CW7R6FYYK9JWWGW0X","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FSKILL.md",[174],{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},[176,177,178,163,179,180,181,106,182,183,157,184,108,185,186,187,188,189,190,191],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":199,"publishedAt":48},"01M71JS4X2FRY41DE84DEP06MN","vercel-react-view-transitions","Guide for implementing smooth, native-feeling animations using React's View Transition API (`\u003CViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter\u002Fexit of components, animate list reorder, implement directional (forward\u002Fback) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-view-transitions\u002FSKILL.md",[198],{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},[187,200,201,202,203,204,205,206,207,181,208,209,210,211,212,186,213,214,215,216],"vercel react view transitions","view","react view transitions","vercel","transitions","shared","back","Animation","types","states","element","implementing","when","api","route","create","libraries",{"skillNo":218,"name":219,"nameZh":6,"description":220,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":221,"categories":222,"keywords":224,"publishedAt":48},"01M71JS1WZ1J4F9YVC2203JBJW","vercel-react-native-skills","React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-native-skills\u002FSKILL.md",[223],{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},[203,225,187,226,227,228,229,230,231,106,232,211,233,108,234,235,212,236,237,186],"vercel react native skills","react native","native","react native skills","modules","platform","animations","performance","triggers","react native components","apps","best practices","tasks"]