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概要と使いどころ
Converts audio objects stored in Volcengine TOS into PCM-oriented WAV output through TOS data-process async jobs. Use this skill when the user needs to convert audio to PCM or WAV, resample audio to 16k, convert to mono, change sample format, normalize audio for ASR pipelines, or prepare TOS audio files for speech recognition — even if they don't explicitly mention 'PCM' or 'audio conversion'.
日本語の概要は準備中です。原文の説明を表示しています。
Compresses and uncompresses file objects stored in Volcengine TOS through TOS data-process async jobs. Use this skill when the user needs to zip files, unzip archives, create tar or zstd archives, extract compressed files, pack multiple TOS objects into a single archive, bundle files together, or distribute files as a package — even if they don't explicitly mention 'compression', 'archive', '打包', or '压缩'.
日本語の概要は準備中です。原文の説明を表示しています。
Transforms and inspects image objects stored in Volcengine TOS. Use this skill only when the task explicitly involves a TOS bucket/object key, TOS image processing, TOS-to-TOS save-as output, or Volcengine TOS image process syntax such as image/info, image/resize, image/format, image/watermark, image/draw, image/blindwatermark, or image/understanding. Do not use this skill for ordinary uploaded screenshots, local images, UI screenshot analysis, generic OCR, face detection, or visual question answering unless the user clearly says the image is a TOS object or asks to process/save it through TOS.
日本語の概要は準備中です。原文の説明を表示しています。
Previews and exports documents stored in Volcengine TOS: generate PDF/PNG/JPG previews, read page counts, resolve HTML preview URLs, and batch-export PDF pages as images. Use this skill when the user needs to convert or preview office documents (Word, Excel, PPT, PDF), export specific pages as images, get document page counts, or generate HTML preview links — even if they don't explicitly mention 'doc-preview' or 'document conversion'.
日本語の概要は準備中です。原文の説明を表示しています。
Removes unwanted visual elements from videos using AI-powered inpainting via Volcengine LAS. Video watermark removal, subtitle removal, logo removal, and text overlay removal — erases and cleans up watermarks, hardcoded subtitles, logos, text, and other fixed-region artifacts and obstructions from video footage. Video inpainting, video repair, video restoration, and video cleanup. Supports specifying exact bounding boxes for targeted removal and erasure. Handles videos up to 4 hours and 30GB. Use this skill when the user wants to remove watermarks from videos, erase hardcoded subtitles/captions, delete logo or text overlays, clean up video footage by removing unwanted objects, repair or restore videos by removing obstructions, do video inpainting on fixed regions, or remove visual artifacts from video content.
日本語の概要は準備中です。原文の説明を表示しています。
Agent self-evolution system. Collects signals from user feedback, stores execution trajectories (golden + correction pairs), analyzes patterns, proposes mutations to workspace files, and generates HTML reports. Trigger with "/evolve" or when the user asks to improve agent behavior. Also use when the user says "remember this pattern", "don't do X again", or "that was a good approach, save it".
日本語の概要は準備中です。原文の説明を表示しています。
Use when building, scaffolding, modifying, debugging, converting, or verifying Apache Flink Agents applications, including Flink Agents YAML, Workflow Agent, ReAct Agent, Actions, Resources, MCP servers, vector stores, runtime skills, Python, or Java. Do not use for ordinary Flink jobs that do not use Flink Agents.
日本語の概要は準備中です。原文の説明を表示しています。
Use when reviewing, designing, or modifying Java enterprise systems that expose, exchange, store, process, export, or port data across users, businesses, connected products, cloud providers, APIs, event streams, AI data pipelines, data spaces, or SaaS platforms and need EU Data Act engineering controls. This should trigger for requests such as Review a Java platform for EU Data Act controls; Design data access and portability evidence; Add data-sharing request workflows, export formats, interoperability, metadata, audit logs, cloud-switching support, non-personal data safeguards, or trade-secret handoffs; Assess Data Act engineering readiness before production release. Part of Plinth Toolkit
日本語の概要は準備中です。原文の説明を表示しています。
Remove AI-generated jargon and restore human voice to text. Built from analyzing 1,000+ AI vs human content pieces.
日本語の概要は準備中です。原文の説明を表示しています。
Incorporate moeru-ai/AUV into native desktop app control through its CLI or connected MCP for observation, targeted input, reusable operations, and verification. Use for native app automation, repeated desktop workflows, or explicit AUV requests.
日本語の概要は準備中です。原文の説明を表示しています。
Generate descriptive commit messages by analyzing git diffs. Use when the user asks for help writing commit messages or reviewing staged changes.
日本語の概要は準備中です。原文の説明を表示しています。
This skill handles file format conversions across documents (PDF, DOCX, Markdown, HTML, TXT), data files (JSON, CSV, YAML, XML, TOML), and images (PNG, JPG, WebP, SVG, GIF). Use when the user requests converting, transforming, or exporting files between formats. Generates conversion code dynamically based on the specific request.
日本語の概要は準備中です。原文の説明を表示しています。
Expert code review specialist for quality, security, and maintainability. Use when reviewing code changes, ensuring high development standards, or conducting security audits. Provides actionable feedback organized by priority.
日本語の概要は準備中です。原文の説明を表示しています。
Remove AI-generated code slop from branches. Use after AI-assisted coding sessions to clean up defensive bloat, unnecessary comments, type casts, and style inconsistencies. Focuses on identifying and removing AI artifacts that degrade code quality.
日本語の概要は準備中です。原文の説明を表示しています。
Security auditing and vulnerability assessment specialist. Use when conducting security reviews, analyzing code for vulnerabilities, performing OWASP assessments, or creating security audit reports.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
日本語の概要は準備中です。原文の説明を表示しています。
Agile ceremonies and sprint management specialist. Use when running standups, retrospectives, sprint planning, or tracking sprint progress.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when demonstrating skill structure and format. Provides example patterns for creating new skills.
日本語の概要は準備中です。原文の説明を表示しています。
Meta-cognitive reasoning specialist for evidence-based analysis, hypothesis testing, and cognitive failure prevention. Use when conducting reviews, making assessments, debugging complex issues, or any task requiring rigorous analytical reasoning. Prevents premature conclusions, assumption-based errors, and pattern matching without verification.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic framework for extracting actionable items from documents and organizing them into prioritized, trackable checklists. Use when converting reports, meeting notes, audits, or any document with embedded action items into structured TODO lists.
日本語の概要は準備中です。原文の説明を表示しています。
Development standards for the Nathan n8n-Jira agent automation system. Covers n8n workflows, Python patterns, and project conventions.
日本語の概要は準備中です。原文の説明を表示しています。
n8n workflow automation patterns and API integration. This skill should be used when creating n8n workflows, using webhooks, managing workflows via REST API, or integrating n8n with MCP servers. Covers workflow JSON structure, node patterns, and automation best practices.
日本語の概要は準備中です。原文の説明を表示しています。
Project-wide coding standards and conventions specialist. Use PROACTIVELY when writing code, making architectural decisions, or establishing project conventions. Covers coding style, commenting, error handling, validation, tech stack consistency, and project conventions across all languages and frameworks.
日本語の概要は準備中です。原文の説明を表示しています。