530건 · 관련도순
Analyze images using Dashscope (Qwen) Vision models for detailed description, OCR text extraction, object recognition, and visual Q&A. Use when the user needs to understand image content via Alibaba Cloud Dashscope API, especially for Chinese-language image analysis and documents.
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使用Nutrient DWS API处理、转换、OCR识别、提取、编辑、签名和填写文档。支持PDF、DOCX、XLSX、PPTX、HTML和图像格式。
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使用 Nutrient DWS API 进行文档处理、转换、OCR、提取、脱敏、签名以及表单填充。支持 PDF、DOCX、XLSX、PPTX、HTML 和图像格式。
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使用 Nutrient DWS API 处理、转换、OCR、提取、脱敏、签名和填充文档。支持 PDF、DOCX、XLSX、PPTX、HTML 和图像。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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When a request is vague, assumption-laden, or "obvious," ask the few load-bearing questions that expose hidden requirements before building or committing.
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dontbesilent 执行力诊断。用阿德勒心理学框架诊断你「知道该做什么但就是不做」的真正原因。 触发方式：/dbs-action、/action、「我知道该怎么做但就是不做」「为什么我总是拖延」 Execution block diagnosis using Adlerian psychology framework. Trigger: /dbs-action, "I know what to do but can't do it", "why do I procrastinate"
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Converts DOCX/PDF/PPTX and saved HTML/HTM to high-quality Markdown with automatic post-processing. Fixes pandoc grid tables, simple tables, image paths, CJK bold spacing, attribute noise, and code blocks; for PDFs also strips OCR garbage blocks, repeated headers/footers/watermarks, and absolute image paths from pymupdf4llm output. Benchmarked best-in-class (7.6/10) against Docling, MarkItDown, Pandoc raw, and Mammoth. Trigger on "convert document", "docx to markdown", "parse word", "doc to markdown", "解析word", "转换文档", "HTML to Markdown".
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Build the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, my AI results are mediocre, or how do I get it right the first time. Produces the specific context this task needs (who/what/constraints/examples/format), a reusable primer you can paste ahead of the request, the difference between a starved prompt and a well-briefed one, and what to leave out — turning vague back-and-forth into a strong first result.
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Assemble a creator picture-in-picture product-listicle ad from a config — the creator stays FULL-FRAME the whole beat (voice plus lips generated together per beat, no separate VO, no cut to a full-frame product shot), and on each product beat three persistent overlays ride on top for the WHOLE beat — a title pill top-center, the DEMO in a rounded PiP window top-right (the brand's real UGC clip MUTED, or for a no-UGC brand the product's own autocropped UI still / screen-recording sized to fill the window), and a bottom product card (rounded thumbnail plus 'N · CATEGORY' small-caps plus product NAME in a serif face). Hook plus CTA beats are the creator full-frame with the title pill only. Assembly builds ONE full-1080x1920 transparent overlay PNG per beat, overlays it on the creator clip (cover-scaled to 1080x1920) for the whole beat keeping the native audio, concats all beats, then burns captions LAST as timed PIL PNG overlays (this ffmpeg has no libass) timed deterministically from the known per-beat script. This is the FREE deterministic assembly stage (overlay-PNG build plus cover-scale composite plus concat plus PIL-PNG caption burn); the creator anchor and the N native talking clips come from create-image-fal (Seedream v5 Pro) and create-video-fal (Seedance 2.0). Use for the creator-pip-listicle format.
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Local vision CLIs: glance (describe/ask/OCR an image), ground (locate a target, pixel box), detect (element inventory), trace (image to SVG geometry), crop (cut a pixel box to a file), and scripts/html_shot.py (HTML file to image). Use for any task involving an image — questions, text, splitting and transcribing long screenshots or chat histories, locating elements, comparing, rebuilding as HTML/SVG, digitizing a sketch or diagram, reading values off a chart, operating a GUI from screenshots — and to re-check an image yourself when a description you were given lacks a detail.
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Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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Deep business diagnosis for when things aren't working. Uses Socratic questioning, first-principles reasoning, and constraint analysis to find WHY a business is stuck — not just prescribe solutions. Use when the user says 'my business isn't working', 'I'm stuck', 'what's wrong', 'diagnose my business', 'why am I not growing', 'help me figure out the problem', or describes a specific business challenge.
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Z.AI CLI providing: - Vision: image/video analysis, OCR, UI-to-code, error diagnosis (GLM-4.6V) - Search: real-time web search with domain/recency filtering - Reader: web page to markdown extraction - Repo: GitHub code search and reading via ZRead - Tools: MCP tool discovery and raw calls - Code: TypeScript tool chaining Use for visual content analysis, web search, page reading, or GitHub exploration. Requires Z_AI_API_KEY.
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Compare several Japanese NLP libraries, models, or datasets for a keyword (a specific tool name, or a function/task like '形態素解析') across a handful of criteria chosen for that comparison, rendered as a ○/△/✕ table. Use when the user wants a side-by-side comparison of multiple Japanese NLP tools/libraries/datasets, not just the single best one. Trigger phrases include 'X と Y と Z を比較して', '形態素解析ライブラリを比較', 'MeCab と Sudachi どっちがいい', 'どのツールを使うべき', 'compare japanese tokenizers', 'mecab vs sudachi vs janome', 'which embedding model should I use', '日本語NERライブラリの比較表', 'pros and cons of japanese OCR tools'. For a single ranked list use search; for alternatives to one specific tool (or contribution candidates) without a multi-axis table, use discover.
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Given a Japanese NLP GitHub repo/model/dataset (URL / owner/repo / tool name) OR a topic, find what's already in awesome-japanese-nlp-resources and discover related resources NOT yet listed (contribution candidates). Mines the bundled dataset, then expands via web research across GitHub and Hugging Face. Use when the user names a SPECIFIC repository, model, or tool and wants alternatives/equivalents, OR wants to discover Japanese NLP resources for a topic that are NOT yet in the list, OR wants to prepare a contribution. Trigger phrases include 'mecabに似たツール', 'fugashiの代替', 'alternatives to fugashi', 'repos like manga-ocr', 'what else is like sudachi', 'リストに無い新しい日本語NLP', 'awesome-japanese-nlpに追加できそうな', '最近公開された日本語NLPツール', 'find unlisted Japanese NLP repos', 'new Japanese models on Hugging Face', 'contribute a new resource'. For a simple lookup of what already exists, use the search skill instead.
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Zoom Out Right — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
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Zoom Out Down — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
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Slide In Left — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
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Slide In Up — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Zoom In Down — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Wobble — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Slide Out Down — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Zoom In Right — a drop-in CSS keyframe animation from Animate.css (Hippocratic-2.1, © Daniel Eden). No JS required. Honors prefers-reduced-motion. Use restrained; attribute Animate.css.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.