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Found 41 Skills
Convert legal texts (legal provisions or legal cases) into standardized Markdown format and remove promotional redundant information. This skill shall be used when users need to process legal provisions (such as the Civil Code, Criminal Law, etc.), organize legal cases (such as typical cases of the Supreme People's Court, judgment documents, etc.), or format legal documents from pasted text. Note: This skill is only responsible for formatting and content cleaning, and does not have content crawling capability. Content acquisition shall be completed by other skills (such as wechat-article-fetch), and AI will automatically determine the skill collaboration sequence.
Ingest any raw text data, conversation logs, chat exports, or unstructured documents into the Obsidian wiki. Use this skill when the user wants to process data that isn't standard documents or Claude history — things like ChatGPT exports, Slack threads, Discord logs, meeting transcripts, journal entries, CSV data, browser bookmarks, email archives, or any raw text dump. Triggers on "ingest this data", "process these logs", "add this export to the wiki", "import my chat history from X". This is the catch-all for any text source not covered by the more specific ingest skills.
Implement Syncfusion ASP.NET Core Inline AI Assist control for real-time text processing and AI-powered features. Use this skill when users need intelligent prompt suggestions, AI-assisted content generation, command popups, response actions, or positioning AI assist popups in ASP.NET Core applications.
An epistemic extraction system that analyzes text to identify its logical structure according to Aristotelian and Objectivist epistemology. Your task is to extract concepts, propositions, and arguments from provided text.
Implement the Syncfusion Angular Inline AI Assist component for AI-powered text processing and editing. Use this skill when user needs to add AI-powered suggestions, create prompt/response workflows, customize toolbars and commands, handle AI responses, configure templates, implement event handling, or add localization to Angular applications with intelligent inline text editing capabilities. Covers installation, configuration, response modes, command settings, toolbar customization, template usage, event handling, methods, and RTL/localization support.
Rewrite specified documents to remove AI-generated traces. Automatically select the most suitable humanization strategy (humanizer-zh / humanize-chinese / technical-writing), and iterate rewriting until the result meets the standard or reaches a maximum of 42 iterations. Suitable for de-AI processing of Chinese texts, including general articles, technical documents, academic papers, etc. Use when user says: "humanize this", "去AI味", "降AIGC", "人性化改写", "改成人话", "去除AI痕迹", "humanize document", "make text human-like", "去机器味", "降低AI率", "过AIGC检测"
Fetch transcripts from YouTube videos for summarization and analysis.
NLTK natural language toolkit. Use for NLP.
Formats text according to specified style guidelines. A clean example skill with no security issues.
Clean and reconstruct raw auto-generated captions (Zoom, YouTube, Teams, Google Meet, Otter.ai, etc.) into readable, coherent transcripts. Use when the user provides raw caption files (.txt, .vtt, .srt), meeting transcripts with timestamps and speaker tags, or asks to clean up/refine a transcript. Handles: timestamp removal, speaker tag normalization, filler word removal, broken sentence reconstruction, transcription error correction, paragraph formation. Preserves every piece of substantive content while removing noise. Trigger phrases: 'clean this transcript', 'refine captions', 'fix this transcript', 'process Zoom captions', 'clean up meeting notes'.
Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.
Analyze a complete literary work into a structured Basic Memory knowledge graph. Covers schema design, entity seeding, chapter-by-chapter processing, cross-referencing, validation, and visualization.