twitter-reader は何をしますか？
Twitter/Xの投稿内容（長文記事、画像、メタデータを含む）を取得します。Claudeがツイートや記事の内容、著者情報、エンゲージメント指標、埋め込みメディアを取得する必要がある場合に使用します。個別の投稿とX記事（長文コンテンツ）に対応し、画像を自動でローカルの添付フォルダにダウンロードし、適切な画像参照を含む完全なMarkdownを生成します。画像を含むX記事ではJinaよりも推奨されます。
Twitter/Xの投稿内容（長文記事、画像、メタデータを含む）を取得します。Claudeがツイートや記事の内容、著者情報、エンゲージメント指標、埋め込みメディアを取得する必要がある場合に使用します。個別の投稿とX記事（長文コンテンツ）に対応し、画像を自動でローカルの添付フォルダにダウンロードし、適切な画像参照を含む完全なMarkdownを生成します。画像を含むX記事ではJinaよりも推奨されます。
このスキルは、Twitter/Xの投稿内容を取得するためのツールです。個別のツイートやX記事（長文コンテンツ）をサポートし、投稿内容、著者情報、エンゲージメント指標、埋め込まれたメディアを取得できます。特に画像を含むX記事において、Jinaよりも優先的に使用されるべきであり、すべての画像を自動でローカルの添付フォルダにダウンロードし、適切な画像参照を含む完全なMarkdownを生成します。これにより、Claudeや他のAIエージェントがTwitter/Xのコンテンツを正確かつ効率的に解析・処理できるようになります。
npx skills add https://github.com/daymade/claude-code-skills/tree/main/skills/twitter-readerInstalled? Explore more 画像 skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
Twitter/Xの投稿内容（長文記事、画像、メタデータを含む）を取得します。Claudeがツイートや記事の内容、著者情報、エンゲージメント指標、埋め込みメディアを取得する必要がある場合に使用します。個別の投稿とX記事（長文コンテンツ）に対応し、画像を自動でローカルの添付フォルダにダウンロードし、適切な画像参照を含む完全なMarkdownを生成します。画像を含むX記事ではJinaよりも推奨されます。
This repo contains 9 individual skills — each has its own dedicated page.
>- Generates Chinese/Japanese speech with StepFun's Contextual TTS — default stepaudio-2.5-tts, stepaudio-3-tts for whisper/inline-() prosody. Replaces step-tts-2's voice_label with natural-language instruction. Use for emotional/prosody-controlled synthesis, batch voice lines, migrating from step-tts-2, or cloned voices (2.5/step-tts-2, not v3). Triggers on 阶跃 TTS, 语音合成, 配音. Not for transcription (use stepfun-asr).
This skill should be used when comparing two videos to analyze compression results or quality differences. Generates interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Triggers when users mention "compare videos", "video quality", "compression analysis", "before/after compression", or request quality assessment of compressed videos.
Download YouTube videos and HLS streams (m3u8) from platforms like Mux, Vimeo, etc. using yt-dlp and ffmpeg. Use this skill when users request downloading videos, extracting audio, handling protected streams with authentication headers, or troubleshooting download issues like nsig extraction failures, 403 errors, or cookie extraction problems.
Entry point for local AI conversation history across providers. Routes a request to the one skill that owns it, by platform (Claude Code, OpenAI Codex, Kimi CLI) and action (read evidence vs continue interrupted work), and owns the one job none of them own alone: a single inventory spanning all three providers. Use when the provider is unknown or plural ("our history", "what have I been working on", "which chats did I have"), when the user wants Kimi CLI history at all, when it is unclear whether they need evidence or resumption, or when they ask for this skill by name. Vague recall that names no platform ("we discussed this once, when was it?") belongs here rather than to a single-provider reader, because a Claude-only answer to an unscoped question cannot support an absence claim. When the platform and the action are both already clear, load that executor skill directly instead — except Kimi CLI, which has no reader or continuation skill of its own and always routes through here.
Create professional slide decks from topics or documents. Generates structured content with data-driven charts, speaker notes, and complete PPTX files. Applies persuasive storytelling principles (Pyramid Principle, assertion-evidence). Supports multiple formats (Marp, PowerPoint). Use for presentations, pitches, slide decks, or keynotes.
Transform vague prompts into precise, well-structured specifications using EARS (Easy Approach to Requirements Syntax) methodology. This skill should be used when users provide loose requirements, ambiguous feature descriptions, or need to enhance prompts for AI-generated code, products, or documents. Triggers include requests to "optimize my prompt", "improve this requirement", "make this more specific", or when raw requirements lack detail and structure.
This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.
Reads, searches, and exports local Claude Code history without resuming work. Covers recent session inventory, exact session timelines, verbatim human input including queued mid-turn prompts, full-event keyword search, hybrid recall when wording changed, end-state triage, and deleted-file recovery across active Claude homes plus registered archives. Use whenever the user asks what they or Claude said, wants a Claude Code session ID or original context, remembers prior work vaguely, needs an old file from a transcript, or must prove what a Claude session contained before continuing it. Also owns the only Kimi CLI surface, via its Kimi inventory and search flags. For Codex history use read-codex-history; when the request names no platform at all or spans providers, start at local-conversation-history.
Reads, searches, and exports local OpenAI Codex history without continuing the old task. Lists recent Codex sessions, extracts exact prompt-ledger inputs by Session, locates a rollout by verified session_meta identity, reconstructs one chronological user/assistant timeline with fork and compaction lineage, and performs bounded keyword search across live and archived rollouts. Use whenever the user asks what they told Codex, wants recent original inputs, a Codex Session ID, full prior context, fork ancestry, or evidence of what a Codex run did. For Claude Code history use read-claude-code-history.
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.