「generate」の検索結果

Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.

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Use GitHub Copilot CLI in non-interactive mode to ask questions, review code, or generate snippets without manual interaction.

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Generate user-facing App Store release notes from git history since the last tag.

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Generate hand-drawn 16:9 article illustrations with the Grav character IP, sparse annotations, and absurd but clear visual metaphors.

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Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real devices.

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Master API documentation with OpenAPI 3.1, AI-powered tools, and modern developer experience practices. Create interactive docs, generate SDKs, and build comprehensive developer portals.

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Generates client SDK code, API wrapper libraries, request/response models, and language-specific usage patterns for any REST API.

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Generate comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices

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Generates complete, production-ready REST API endpoint specifications for any system or domain the user describes.

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Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.

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Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.

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Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

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根据主题、正文或已有标题生成并筛选小红书标题，提供改写和 A/B 方案，同时检查账号调性、真实性以及正文能否兑现标题承诺。用户要起标题、改标题、套用标题模式或检查标题时使用。 English: Generate and filter Xiaohongshu titles from a topic, draft, or existing title, offering rewrites and A/B options while checking voice, truthfulness, and whether the content fulfills the promise. Use to write, improve, pattern-match, or review titles.

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把已验证的传播机制转成适合目标账号的内容选题，并完成生成、迁移、评分和筛选，让选题自然连接人设、产品或门店。用户要从低粉爆款、垂直样本、邻近受众或跨赛道内容中寻找新选题时使用。 English: Turn validated content mechanisms into topics that fit the target account, then generate, adapt, score, and filter them while connecting naturally to the persona, product, or store. Use to find ideas from low-follower breakouts, niche examples, adjacent audiences, or other categories.

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RBG controller stress test - deploy kwok in existing cluster, run create/update/delete load tests with real controller pod, collect pprof profiling and logs, generate analysis report with recommendations

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Create professional, consultant-grade PowerPoint presentations from scratch using MckEngine (python-pptx wrapper) with McKinsey-style design. Use when user asks to create slides, pitch decks, business presentations, strategy decks, quarterly reviews, board meeting slides, or any professional PPTX. AI calls eng.cover(), eng.donut(), eng.timeline() etc — 67 high-level methods across 12 categories (structure, data, framework, comparison, narrative, timeline, team, charts, images, advanced viz, dashboards, visual storytelling), consistent typography, zero file-corruption issues, BLOCK_ARC native shapes for circular charts (donut, pie, gauge), production-hardened guard rails for spacing, overflow, legend consistency, title style uniformity, dynamic sizing for variable-count layouts, horizontal item overflow protection, chart rendering, and AI-generated cover images via Tencent Hunyuan 2.0 with professional cutout, cool grey-blue tint, and McKinsey-style Bézier ribbon decoration.

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Use when switching AI persona/language style. Syncs 13+ character profiles (Ding Yuanying, Lin Daiyu, Lu Xun, Li Yunlong, etc.) from GitHub, generates persona prompts with thinking patterns, rhetoric, and speech traits.

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Remove signs of AI-generated writing from prose, and keep it out of a repo. Use when drafting, editing, or reviewing text to make it sound natural and human, or when auditing a whole docs folder for AI slop. Detects 41 patterns across content, language, style, communication, filler, and rhetoric, including: significance inflation, promotional language, -ing tails, vague attributions, AI vocabulary, copula avoidance, negative parallelisms, false agency, em dash overuse, chatbot artifacts, hedging stacks, staccato drama, and aphorism formulas. Includes voice calibration, a no-fabrication rule, statistical tells, and a draft -> audit -> final rewrite loop.

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Write RULES.md, the project standards the AI must follow, with registry-verified dependency versions and permanent rule IDs.

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Break the PRD into sequenced implementation RFCs under RFCs/ with an RFCS.md index, then cold-read each RFC for gaps.

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Maintenance of the contributor issue pipeline for JSONbored/awesome-claude (HeyClaude) — closing issues that are already done but not marked so, and keeping a small, high-value contributor-available backlog stocked with real website/content/feature/bugfix work. Runs every ~24h via a dedicated scheduled task. Invoke for "run the issue gardening", "audit open issues for stale/complete ones", "generate new contributor issues", or any recurring/scheduled run of this process. `reference.md` (next to this file) has the exhaustive label/milestone/ template detail — read it before doing real work, not just this file. This is the awesome-claude-specific instance; JSONbored/loopover and JSONbored/metagraphed each have their own separate copy with different conventions and a much larger backlog target — do not cross-apply either repo's specifics to this one without being asked.

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Educator peer review management for Canvas LMS. Tracks completion rates, analyzes comment quality, flags problematic reviews, sends targeted reminders, and generates instructor-ready reports. Trigger phrases include "peer review status", "how are peer reviews going", "who hasn't reviewed", "review quality", or any peer review follow-up task.

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。