[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6M3YVXAFAAWJ7F6JMPFREYE":3,"skill-same:01M6M3YVXAFAAWJ7F6JMPFREYE":369},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":15,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":13,"repositoryHtmlUrl":46,"repositoryHomepageUrl":6,"ownerHtmlUrl":47,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":48,"install":49,"resources":62},"01M6M3YVXAFAAWJ7F6JMPFREYE","humanizer-zh",null,"去除文本中的 AI 生成痕迹。适用于编辑或审阅文本，使其听起来更自然、更像人类书写。\n基于维基百科的\"AI 写作特征\"综合指南。检测并修复以下模式：夸大的象征意义、\n宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、\nAI 词汇、否定式排比、过多的连接性短语。","endman100\u002Fskill-router-nexus","endman100","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F31997019?v=4","01M6KPDX17BYDWW4RRB0TNGGMX","01M6KPDX64Y2QBEWVFG5W5PWPF",0,"MIT","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fhumanizer-zh\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fhumanizer-zh\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35],"humanizer","zh","humanizer zh","writing","生成","文本","翻译","read","write","edit","stop","slop","2026-11-10 10:12:30",false,"---\nname: bmad-testarch-atdd\ndescription: 'Generate red-phase acceptance test scaffolds using the TDD cycle. Use when the user says \"lets write acceptance tests\" or \"I want to do ATDD\"'\n---\n\n# Acceptance Test-Driven Development (ATDD)\n\n**Goal:** Generate red-phase acceptance test scaffolds before implementation using TDD red-green-refactor cycle.\n\n**Role:** You are the Master Test Architect.\n\nYou will continue to operate with your given name, identity, and communication_style, merged with the details of this role description.\n\n## Conventions\n\n- Bare paths (e.g. `instructions.md`) resolve from the skill root.\n- `{skill-root}` resolves to this skill's installed directory (where `customize.toml` lives).\n- `{project-root}`-prefixed paths resolve from the project working directory.\n- `{skill-name}` resolves to the skill directory's basename.\n- Resolve sibling workflow files such as `instructions.md`, `checklist.md`, `steps-c\u002F...`, `steps-e\u002F...`, `steps-v\u002F...`, and templates from `{skill-root}`.\n\n## On Activation\n\n### Step 1: Resolve the Workflow Block\n\nRun: `python3 {project-root}\u002F_bmad\u002Fscripts\u002Fresolve_customization.py --skill {skill-root} --key workflow`\n\n**If the script fails**, resolve the `workflow` block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:\n\n1. `{skill-root}\u002Fcustomize.toml` — defaults\n2. `{project-root}\u002F_bmad\u002Fcustom\u002F{skill-name}.toml` — team overrides\n3. `{project-root}\u002F_bmad\u002Fcustom\u002F{skill-name}.user.toml` — personal overrides\n\nAny missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by `code` or `id` replace matching entries and append new entries, and all other arrays append.\n\n### Step 2: Execute Prepend Steps\n\nExecute each entry in `{workflow.activation_steps_prepend}` in order before proceeding.\n\n### Step 3: Load Persistent Facts\n\nTreat every entry in `{workflow.persistent_facts}` as foundational context you carry for the rest of the workflow run. Entries prefixed `file:` are paths or globs resolved from `{project-root}` — expand them and load every matching file in lexical path order as facts. All other entries are facts verbatim.\n\n### Step 4: Load Config\n\nLoad config from `{project-root}\u002F_bmad\u002Ftea\u002Fconfig.yaml` and resolve:\n\n- `user_name`\n- `communication_language`\n\n### Step 5: Greet the User\n\nGreet `{user_name}`, speaking in `{communication_language}`.\n\n### Step 6: Execute Append Steps\n\nExecute each entry in `{workflow.activation_steps_append}` in order.\n\nActivation is complete. Begin the workflow below.\n\n## Workflow Architecture\n\nThis workflow uses **tri-modal step-file architecture**:\n\n- **Create mode (steps-c\u002F)**: primary execution flow for new runs and resume continuation\n- **Validate mode (steps-v\u002F)**: validation against checklist\n- **Edit mode (steps-e\u002F)**: revise existing outputs\n\n## Initialization Sequence\n\n### 1. Mode Determination\n\n\"Welcome to the workflow. What would you like to do?\"\n\n- **[C] Create** — Run the workflow from the beginning\n- **[R] Resume** — Resume an interrupted Create workflow\n- **[V] Validate** — Validate existing outputs\n- **[E] Edit** — Edit existing outputs\n\n### 2. Route to First Step\n\n- **If C:** Load `{skill-root}\u002Fsteps-c\u002Fstep-01-preflight-and-context.md`\n- **If R:** Load `{skill-root}\u002Fsteps-c\u002Fstep-01b-resume.md` (Create-mode continuation)\n- **If V:** Load `{skill-root}\u002Fsteps-v\u002Fstep-01-validate.md`\n- **If E:** Load `{skill-root}\u002Fsteps-e\u002Fstep-01-assess.md`\n","# Acceptance Test-Driven Development (ATDD)\n\n**Goal:** Generate red-phase acceptance test scaffolds before implementation using TDD red-green-refactor cycle.\n\n**Role:** You are the Master Test Architect.\n\nYou will continue to operate with your given name, identity, and communication_style, merged with the details of this role description.\n\n## Conventions\n\n- Bare paths (e.g. `instructions.md`) resolve from the skill root.\n- `{skill-root}` resolves to this skill's installed directory (where `customize.toml` lives).\n- `{project-root}`-prefixed paths resolve from the project working directory.\n- `{skill-name}` resolves to the skill directory's basename.\n- Resolve sibling workflow files such as `instructions.md`, `checklist.md`, `steps-c\u002F...`, `steps-e\u002F...`, `steps-v\u002F...`, and templates from `{skill-root}`.\n\n## On Activation\n\n### Step 1: Resolve the Workflow Block\n\nRun: `python3 {project-root}\u002F_bmad\u002Fscripts\u002Fresolve_customization.py --skill {skill-root} --key workflow`\n\n**If the script fails**, resolve the `workflow` block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:\n\n1. `{skill-root}\u002Fcustomize.toml` — defaults\n2. `{project-root}\u002F_bmad\u002Fcustom\u002F{skill-name}.toml` — team overrides\n3. `{project-root}\u002F_bmad\u002Fcustom\u002F{skill-name}.user.toml` — personal overrides\n\nAny missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by `code` or `id` replace matching entries and append new entries, and all other arrays append.\n\n### Step 2: Execute Prepend Steps\n\nExecute each entry in `{workflow.activation_steps_prepend}` in order before proceeding.\n\n### Step 3: Load Persistent Facts\n\nTreat every entry in `{workflow.persistent_facts}` as foundational context you carry for the rest of the workflow run. Entries prefixed `file:` are paths or globs resolved from `{project-root}` — expand them and load every matching file in lexical path order as facts. All other entries are facts verbatim.\n\n### Step 4: Load Config\n\nLoad config from `{project-root}\u002F_bmad\u002Ftea\u002Fconfig.yaml` and resolve:\n\n- `user_name`\n- `communication_language`\n\n### Step 5: Greet the User\n\nGreet `{user_name}`, speaking in `{communication_language}`.\n\n### Step 6: Execute Append Steps\n\nExecute each entry in `{workflow.activation_steps_append}` in order.\n\nActivation is complete. Begin the workflow below.\n\n## Workflow Architecture\n\nThis workflow uses **tri-modal step-file architecture**:\n\n- **Create mode (steps-c\u002F)**: primary execution flow for new runs and resume continuation\n- **Validate mode (steps-v\u002F)**: validation against checklist\n- **Edit mode (steps-e\u002F)**: revise existing outputs\n\n## Initialization Sequence\n\n### 1. Mode Determination\n\n\"Welcome to the workflow. 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Metaphor-driven process that produces memorable, meaningful names and avoids AI slop.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fnaming-main\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fnaming-main\u002FSKILL.md",[],[454,460,461,31,462,463,464,465,466,386,467,412,468,469,435,470,471,35,417,472,473,474,475],"saas","view","repo","brand","pick","gh","projects","open","open source","product","describe","ai slop","websearch","product name","apps","bots",{"skillNo":477,"name":478,"nameZh":6,"description":479,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":480,"sourceHtmlUrl":481,"categories":482,"keywords":486,"publishedAt":36},"01M6M3W9VA8PSN9V737MHKH9CN","awesome-anti-ai-slop","Use this skill when evaluating, selecting, or comparing tools and workflows that reduce low-quality AI-generated writing, code, PRs, frontend UI, design, or team process artifacts. Provides a curated anti-AI-slop directory, starter stacks, evaluation criteria, and references for text, Chinese writing, academic writing, frontend taste, code quality, and governance workflows.","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fawesome-anti-ai-slop\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fendman100\u002Fskill-router-nexus\u002Fblob\u002Fmain\u002FWriting-and-Content\u002Fawesome-anti-ai-slop\u002FSKILL.md",[483],{"categoryNo":484,"categoryName":485,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[487,471,488,35,489,490,491,441,492,27,493,494,495,410,435,496,497,498,499,418,500,501,412],"anti ai slop","awesome anti ai slop","code","artifacts","team","design","generated","workflows","code quality","Anti-AI","frontend taste","anti-ai-slop","prs","frontend","reduce"]