基于历史数据利用统计分析方法预测下一组数字,严格遵守前5位(1-35)和后2位(1-12)的范围限制,输出简洁的预测结果。
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。
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基于历史数据利用统计分析方法预测下一组数字,严格遵守前5位(1-35)和后2位(1-12)的范围限制,输出简洁的预测结果。
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 AI art prompt engineer for Midjourney and Stable Diffusion. Generates high-quality prompts including unified batch illustrations, marketing designs, interactive compositions, and structured framework prompts with translations.
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。
提供JavaScript代码,将字符串变量(如Vue3中的ingredients.value)中的所有中文逗号(,)替换为英文逗号(,),用于数据清洗或格式统一。
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。
Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.
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。
Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
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。
Converts X (Twitter) tweets and articles to markdown with YAML front matter. Uses reverse-engineered API requiring user consent. Use when user mentions "X to markdown", "tweet to markdown", "save tweet", or provides x.com/twitter.com URLs for 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。
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
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。
Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI generation.
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。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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 facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
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 images to WebP (default) or PNG with automatic tool selection. Use when user asks to "compress image", "optimize image", "convert to webp", or reduce image file size.
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。
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration), ImageMagick (image manipulation, format conversion, batch processing, effects, composition), and RMBG (AI-powered background removal). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, removing backgrounds from images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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。
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
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 this skill immediately when the user mentions merge conflicts that need to be resolved. Do not attempt to resolve conflicts directly - invoke this skill first. This skill specializes in providing a structured framework for merging imports, tests, lock files (regeneration), configuration files, and handling deleted-but-modified files with backup and analysis.
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。
Apply systematic performance optimization techniques when writing or reviewing code. Use when optimizing hot paths, reducing latency, improving throughput, fixing performance regressions, or when the user mentions performance, optimization, speed, latency, throughput, profiling, or benchmarking.
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。
Anchor your identity on the Autonomys Network so you can always be found — and always come back. Works with agents powered by Claude, GPT, Gemini, and Your agent always comes back. Anchor identity and memory on-chain so any new instance can resurrect from just an address — no local state, no single point of failure. Permanent identity and recovery on the Autonomys Network.
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。
上层编排 Skill,通过 **Brave Search 发现 → 智能选择浏览器截图** 完成结构化素材采集。 文章素材收集编排Skill。为MediaClaw内容生产提供结构化的多平台素材采集workflow。 强制使用OpenClaw Browser截图实际文章页面,支持GitHub/Reddit/X/Medium/知乎等。 用法: (1) content-ops-toolkit素材阶段调用 (2) daily-*-content素材采集 (3) 独立素材收集任务。 Trigger: "收集素材", "素材收集", "采集素材", "素材", "找素材", "research materials", "material collect". Author: Daniel Li version: 2.1.0 dependencies: [brave-search, web-content-capture]
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。
Indestructible agent memory — permanently stored, never lost. Save decisions, identity, and context as a memory chain on the Autonomys Network. Rebuild your full history from a single CID, even after total state loss.
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。
A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
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。
Format SPAWN REQUEST messages to launch parallel agents, generate structured agent status reports, and define communication protocols within the sprint system. Use when the user needs to coordinate multiple agents, format spawn requests, produce agent reports, or establish inter-agent communication patterns.
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。
Google SRE (Site Reliability Engineering) practices distilled from the SRE book series and real Google Brain/Meta/ByteDance production experience. Covers SLI/SLO/Error Budget design, incident response, capacity planning, toil automation, monitoring golden signals, and chaos engineering principles. USE WHEN: designing reliability targets, setting up monitoring/alerting, planning capacity, reducing operational load, building incident response runbooks, implementing chaos engineering, defining error budgets, or establishing reliability culture that balances velocity with stability.
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 performance profiling and optimization methodology. Covers CPU profiling, memory profiling, heap analysis, goroutine/thread analysis, FlameGraph generation, latency profiling, database query profiling, network I/O profiling, and continuous performance regression detection. USE WHEN: investigating performance issues, optimizing slow code, reducing memory usage, diagnosing GC/CPU bottlenecks, finding N+1 queries, analyzing pprof/flamegraph output, or establishing a performance baseline. Triggers on "profiling", "performance analysis", "slow code", "flame graph", "pprof", "heap dump", "memory leak", "CPU spike", "bottleneck".
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。
Architecture Decision Records (ADR) — a lightweight method for capturing important architectural decisions with context, trade-offs, and rationale. Based on Michael Nygard's ADR pattern and Google/Meta/ByteDance's design documentation culture. USE WHEN: deciding between technology choices, designing new architecture, changing existing architecture, documenting why a decision was made, onboarding new team members, or preserving design context for future maintainers. Triggered by terms like "tech choice", "architecture decision", "why did we choose", "design rationale", "ADR", or "architectural decision record".
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。
Fetch personalized daily horoscope forecasts from zodiac-today.com API based on natal chart calculations. Use when a user wants: (1) daily guidance on what activities to pursue or avoid, (2) life planning help — best days for interviews, travel, romance, important decisions, (3) energy/focus/luck/romance forecasts to optimize their schedule, (4) lucky colors and numbers for the day, (5) future date analysis for planning events, trips, or milestones (paid tiers). Triggers: horoscope, zodiac, star sign forecast, daily guidance, lucky day, best day to, astrology advice, what should I do today, is today a good day for, plan my week astrology. Required env: ZODIAC_API_KEY (hsk_ API key), ZODIAC_PROFILE_ID (birth chart profile ID). Collects sensitive PII (email, birth date, birth city) for natal chart — requires user consent.
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。