Results for “markdown”

Summarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).

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Convert the canonical markdown+JSON deliverable of any SfSkills runtime agent into Excel, PDF, CSV, Notion card, ServiceNow ticket, or similar downstream format without adding dependencies to the consumer's project. NOT for an Agentforce action's output — use agentforce/agent-actions. NOT for exporting Salesforce data — use integration/bulk-api-2-patterns.

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Generate a PR_MESSAGE.md file from session context using GitHub CLI. Detects related issues via branch-keyword search, writes a structured PR description with commit subject, summary, test plan, and changelog. Validates with commitlint and markdownlint. Use when preparing a pull request on GitHub.

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Convert any pile of documents (PDF, Word, HTML pages, wiki exports, PowerPoint slides) into clean, LLM-ready markdown context: inventories the sources, picks the right extractor per file type (pdftotext or PyMuPDF for PDF, pandoc or mammoth for docx, readability extraction for HTML.

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Analyze an inventory allocation system for demand-driven distribution accuracy, store clustering methodology, safety stock optimization, markdown timing, replenishment logic, and omnichannel inventory visibility..

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Audit a dynamic pricing engine for revenue optimization and fairness. Evaluates price elasticity models, competitive intelligence feeds, promotional ROI, markdown optimization, price image management, and legal compliance including Robinson-Patman and price gouging regulations..

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Analyzes apparel demand prediction systems for trend forecasting, size curve optimization, color and style analytics, sell-through rate tracking, and markdown optimization following CPFR collaborative planning and GTIN product identification standards..

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Audit and fix agent readiness: the Lighthouse Agentic Browsing fraction, accessibility tree for agents, robots.txt and Content-Signal for AI agents, WAF treatment of agent traffic, llms.txt, Markdown delivery, ai-catalog.json, /.well-known discovery files, and WebMCP tools. Exclude AI citability and brand signals (seo-geo) and commerce protocol depth (seo-ecommerce).

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Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and evidence-backed explanations. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".

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Write a new blog article from scratch for Google rankings and AI citations, then take it through the delivery gates. Generates the full article with template selection, answer-first formatting, Key Takeaways box, sourced statistics, licensed images, built-in SVG charts, optional FAQ and internal linking, in MDX, markdown or HTML. Use when the user asks to write a new blog post or article from a topic or brief ("write a blog post", "draft a new article", "/blog write"). Not for editing an existing post (blog-rewrite), and not for a standalone outline, brief or research request.

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Render Markdown, HTML, or PDF paid-advertising reports from a validated Claude Ads JSON run bundle. Use for ads report, client report, audit PDF, executive audience reporting, or exporting prior audit and plan results.

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Rewrite and optimize existing blog posts for Google SEO (May 2026 Core Update, E-E-A-T) and AI citation visibility as one SEO discipline. For AI-citation-only audit (no Google work), use blog-geo instead. Replaces fabricated statistics with sourced data, applies answer-first formatting, adds images, generates SVG charts, and updates modified dates only for substantive changes. Works with any blog format (MDX, markdown, HTML). Use when user says "rewrite blog", "optimize blog", "update blog", "improve blog", "fix blog".

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Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

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BA (Business Analyst) agent. Analyzes requirements and produces 4 artifact files: requirements.md, user-stories.md, acceptance-criteria.md, business-rules.md. Use --spec <path> to load requirements from any markdown file. Part of the Virtual Team Skill pipeline.

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Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

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美国加州消费者隐私法（CCPA/CPRA）合规检查、风险评估和文档生成工具。 为涉及加州消费者数据的业务提供全面的CCPA/CPRA合规解决方案。 Use when: 需要进行CCPA/CPRA合规自查、消费者权利保障检查、选择退出机制实现、 数据销售合规检查、服务提供商管理、隐私合规体系建设。 🎉 版本1.0.5重要更新： - 🔧 全新统一化CLI接口，与PIPL、GDPR工具体验一致 - 📊 支持JSON/Markdown/HTML/CSV多格式报告输出 - 🚀 跨法域检查：可与PIPL、GDPR配合使用 - 🔒 纯本地运行，零外部依赖 触发关键词：CCPA、CPRA、加州合规、消费者隐私、数据保护、美国合规、 California privacy、Do Not Sell、消费者权利、选择退出 适用范围：美国加州消费者隐私法（CCPA）/ 加州隐私权法案（CPRA） 运行模式：纯本地，无网络请求 ❎ 外部依赖：无（仅Python标准库）⭐

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阿拉丁·AI短剧数字人肖像权合规工坊把「AI 演员/数字人/换脸/声音克隆做完却因肖像权没授权被投诉下架、数字人授权到期还在用、授权只买了一个平台却全网发、AI 形象神似明星惹官司、被举报时拿不出授权链举证」升级成一条纯本地零依赖的上架前置授权链自查工具链：多源导入(drama-cast 角色卡 _cast.json 双契约兼容/人物资产类型声明 assets.json/授权凭证登记 CSV 或 JSON/drama-publish 发行计划 _publish_plan.json 抽平台)→人物资产五分类(AI原创 ai_original/真人出演 real_actor/第三方数字人 digital_human/换脸 face_swap/声音克隆 voice_clone)逐类判定所需授权→10 条确定性授权链规则(A1缺授权凭证 A2要素缺失 A3已过期 A4即将到期 A5平台越界 A6用途越界 A7撞脸公众人物 A8声音克隆缺授权 A9转授瑕疵 A10平台报备缺失)→门禁评分(P0=25/P1=8/P2=3 扣分，100分制 A-D 档，READY可提审/REVIEW建议整改/BLOCK禁止上架)→自包含 HTML 授权链看板(门禁灯+逐条命中+整改建议)+Markdown 整改清单(可直接交制片执行)+feedback 回灌契约(缺证角色回灌 drama-cast 补授权、越界平台回灌 drama-publish 调发行、续签观察名单、报备提醒)。与 aladin-drama 系列闭环衔接(cast/publish 进，整改反馈回灌 cast 补授权、publish 调发行矩阵)。区别于内容合规工具只扫违禁词与画面红线：本款专管「人」的授权链(肖像权/声音权/数字人许可/换脸源授权)，确定性规则可复算、命中带人物名与整改方向、纯本地零依赖零API、授权信息不出本机(法务资产敏感)。触发词：短剧肖像权、数字人授权、换脸授权、声音克隆授权、AI演员合规、肖像授权到期、授权链自查、撞脸明星、数字人合规、AI形象报备、肖像权侵权、portrait rights、digital human license、face swap consent、voice clone authorization、AI短剧、阿拉丁短剧、短剧创作闭环。

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Checks and fixes Chinese copywriting with autocorrect-backed workflows for text and single-file Markdown/TXT inputs. Use when user asks to normalize Chinese punctuation, spacing, or full-width/half-width usage. Also triggers for "校对", "检查排版", "中英文空格", "全角半角". Does not rewrite document structure, product claims, or UI messaging.

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This skill should be used when the user gives a SaaS product's landing page URL, homepage, or name and asks for a full teardown or deep-dive of how the product works across web, desktop, and mobile — including per-platform feature inventories and user journeys, tech stack, pricing/plan mapping, how the platforms integrate and sync (and the business logic behind those choices), hardware integrations, business-scale/revenue signals, and concrete release artifacts per platform — with a structured Markdown report as the deliverable. Trigger on phrases like "research this SaaS", "do a platform teardown of X", "map every feature of this product across web/mobile/desktop", "reverse-engineer how this app works everywhere", or a bare URL plus a request to understand the whole product.

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Convert Claude's Markdown output to each channel's native text syntax before delivery. Adds zero-dependency formatting for WhatsApp, Telegram, and Slack (marker substitution). Also ships a Signal rich-text helper (parseSignalStyles) used by the Signal skill.

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Turn the git commits for a Jira ticket into a short, business-friendly implementation report and save it as local markdown. Use when the user wants to report finished work on a Jira ticket: a Jira report, update, or comment, a summary of their commits or changes for the ticket, or a note telling PM/QA what shipped.

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Draft the QA scope and plain-language test scenarios for a Jira ticket — brief one-liners with automated test references by default, or full Given/When/Then steps — built from the full ticket, the decisions made in its comments, and the actual code change read commit by commit (open PR, the ticket's merged PR, the branch against its base, or a named commit range). Saves a Markdown draft under docs/, iterates with the user, then posts it to the ticket as a new Jira comment only after explicit approval. Use on "QA scope for PROJ-123", "what should QA test", "write test scenarios for QA", "hand this ticket to QA", "prep the QA handoff", "gherkin scenarios for this ticket", or when a branch is ready for manual testing — even when the user only names the ticket or says "this branch".

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Use when working with Nuxt Content v3, markdown content, or CMS features in Nuxt - provides collections (local/remote/API sources), queryCollection API, MDC rendering, database configuration, NuxtStudio integration, hooks, i18n patterns, and LLMs integration

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Generate production-ready API documentation from endpoint descriptions. Outputs OpenAPI 3.0, markdown reference docs, and SDK quickstart guides.

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