读取、搜索和导出本地 OpenAI Codex 历史记录，而无需继续旧任务。
此技能允许用户读取、搜索和导出本地 OpenAI Codex 历史记录，无需继续旧任务。它能够列出最近的 Codex 会话，通过会话提取精确的提示-账本输入，根据经过验证的会话元身份定位滚动记录，重建包含分支和压缩谱系的用户/助手时间线，并在活动存档中执行有界关键词搜索。当用户询问他们曾告诉 Codex 的内容、需要最近的原始输入、Codex 会话 ID、完整的先前上下文、分支谱系或证据证明某个 Codex 运行做了什么时，可以使用此技能。它适用于 OpenAI Codex 本地历史数据，不适用于 Claude Code。
npx skills add https://github.com/daymade/claude-code-skills/tree/main/daymade-claude-code/read-codex-history读取、搜索和导出本地 OpenAI Codex 历史记录，而无需继续旧任务。列出最近的 Codex 会话，通过精确的提示-账本输入提取会话，根据经过验证的会话元身份定位滚动记录，重建包含分支和压缩谱系的用户/助手时间线，并在活动存档中执行有界关键词搜索。当用户询问他们曾告诉 Codex 的内容、需要最近的原始输入、Codex 会话 ID、完整的先前上下文、分支谱系或证据证明某个 Codex 运行做了什么时，请使用此技能。对于 Claude Code 历史记录，请使用 read-claude-code-history。
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.
Fetch Twitter/X post content including long-form Articles with full images and metadata. Use when Claude needs to retrieve tweet/article content, author info, engagement metrics, and embedded media. Supports individual posts and X Articles (long-form content). Automatically downloads all images to local attachments folder and generates complete Markdown with proper image references. Preferred over Jina for X Articles with images.
ElevenLabs text-to-speech with mac-style say UX.
Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine.
Capture and automate macOS UI with the Peekaboo CLI.
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".