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Found 819 Skills
CRITICAL RULE: You MUST use this skill whenever the task involves any machine learning tasks or data analysis. Use this skill if the user's prompt or requirements mention any of the following: * Clustering * Classification * Regression * Time series forecasting * Statistical testing * Model comparison * ML * Data analysis SQL/BigQuery ML HANDOFF: If the user requires a SQL solution, use this skill to dictate the ANALYSIS STEPS (e.g., markdown analysis cells, visualization logic), but defer to `bigquery` for all SQL syntax.
Handle Word document (.docx) creation, editing, and analysis with high-fidelity visual review. Use for professional reports, legal documents, and tracked changes. Use proactively when quality and precise formatting are critical. Examples: - user: "Create a professional report in Word" -> use python-docx with render loops - user: "Draft a legal contract with redlines" -> use ooxml redlining workflow - user: "Extract text from this DOCX while preserving structure" -> use pandoc markdown conversion
Interview-driven automation design tool. This skill should be used when the user wants to design a new skill, agent, automation, shortcut, or any other automatable workflow. Runs a coverage-driven JTBD interview (text or voice), then exports a one-page markdown spec plus an SVG design map.
Create standalone beginner tutorial packages from a topic or supplied references, with adaptive research, course-style outline design, chapter visuals, and Markdown/DOCX/PDF/HTML exports. Use for textbook-like tutorials, course guides, teaching documents, or long beginner guides; not for quick answers, link summaries, pure diagrams, or file conversion.
Polish and elevate MBA thesis/dissertation to the quality of National Excellent Thesis. Conduct comprehensive enhancements in academic language, argument structure, logical rigor, innovation highlights, and formatting. Input: Markdown-formatted thesis text. Output: fully polished complete text. This service is also triggered when the user mentions terms such as "thesis polishing", "MBA thesis", "excellent thesis", "thesis polish", "dissertation improvement", "academic polishing".
微信公众号文章抓取与导出。自动处理 mp.weixin.qq.com 的登录态获取与续期， 支持按公众号搜索、抓取文章列表与正文、按日期窗口导出 Markdown / JSON / CSV。 Trigger when the user wants to crawl a WeChat public account, export recent articles, or 提到 "wcx"、"微信公众号"、"公众号文章"、"mp.weixin"、"抓公众号"、 "crawl wechat official account"、"wxmp"、"最近十天的文章"。
Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.
Audit Android Jetpack Compose repositories for performance, state management, side effects, and composable API quality. Scans source code, scores each category from 0-10, writes a strict markdown report, and summarizes the most important fixes. Use when reviewing a Compose codebase, rating repository quality, inspecting recomposition/state issues, or running a Compose audit.
Facilitate methodical review of proposals (technical designs, product specs, feature requests). Use when asked to "review this proposal", "give feedback on this doc", "help me review this RFC", or when presented with a document that needs structured feedback. Handles markdown files, GitHub gists/issues/PRs, and other text formats. Chunks proposals intelligently, predicts reviewer reactions, and produces feedback adapted to the proposal's format.
Build a retrospective or forward-looking work timeline from git commits, project docs, user notes, or chat records, then output a Markdown and/or HTML report with a Gantt chart or timeline visualization. Use when the user wants to review past work across one or more projects, explain time allocation to a mentor, summarize what was done in a period, or plan the next phase with a timeline.
Review a pull request or contribution deeply, explain it tutorial-style for a maintainer, and produce a polished report artifact such as HTML or Markdown. Use when asked to analyze a PR, explain a contributor's design decisions, compare it with similar systems, or prepare a merge recommendation.
Upgrade a coded website to award-tier, editorially-crafted design using fal.ai. Takes a local HTML file or a dev-server URL, screenshots it, has an opus-4.7 vision model write a gpt-image-2 edit prompt, uses fal-ai/gpt-image-2/edit to produce the redesigned reference image, then opus-4.7 vision writes a Markdown build-spec with a "Hard constraints" section + a tokens.json. Also supports iterate (screenshot implemented site → delta-spec vs reference) and greenfield generate (brief → mockup → single-file HTML). Invoke when the user says "improve the design", "make it world-class", "redesign this landing page", "upgrade this site", "design pass", or points at a local HTML / dev server for a visual review.