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Searches and recovers Claude Code JSONL history across all active config homes and archives registered in ~/.claude/history-sources.json. Use --all-projects when the project is unknown and --codex to include Codex rollout search. Uses internal timestamps and searches messages, thinking, tool inputs/results, queues, attachments, summaries, titles, and file-history paths. Recovers exact captured bytes from Claude file-history snapshots, including post-Write edits and binary files; otherwise labels Write checkpoints as lower fidelity. Use for keyword/date-bounded history search, prior-conversation forensics, deleted-file recovery, vanished ~/.claude/jobs artifacts, tool/file-operation analysis, or requests mentioning session history, find in history, previous conversation, or .claude/projects. For a recent Claude+Codex inventory, use local-conversation-history instead.
Corrects speech-to-text transcription errors using dictionary rules and Claude's built-in AI (no external API key required — Native AI Correction is the DEFAULT). Stage 1 alone is not the job. Stage 3 API is a backup for automation without Claude Code. Builds personalized correction databases that learn from each fix, auto-loads person-name ASR variants from your people roster, and reads per-domain context files that prime the AI pass for context-dependent homophones. Triggers when working with ASR/STT output containing recognition errors, homophones, garbled technical terms, person-name errors, or Chinese/English mixed content. Also triggers on requests to clean up meeting notes, lecture transcripts, interview recordings, or any text produced by speech recognition. Use this skill even when the user just says "fix this transcript", "clean up these meeting notes", or mentions garbled names without invoking ASR specifically.
AWS Well-Architected Security Assessment Tool MCP Server
Generate Chinese / Japanese speech with StepFun's stepaudio-2.5-tts — Contextual TTS that replaces step-tts-2's voicelabel with natural-language instruction (≤200 chars) plus inline () parentheses for句内 prosody. Use when the user wants emotional / prosody control over voice synthesis (whisper, pause, stress, mood pivot mid-sentence), batch-generates game / app voice lines, migrates from step-tts-2 (the voicelabel → instruction breaking change), or hits StepFun's stricter 2.5-era censorship (死/消失/political terms). Triggers on 阶跃 TTS, StepAudio 合成, 语音合成, 配音, 文本转语音, TTS 升级, 迁移 step-tts-2. For transcription with the sibling stepaudio-2.5-asr model, use the stepfun-asr skill instead.
Transcribe audio with StepFun's stepaudio-2.5-asr — an SSE endpoint (NOT /v1/audio/transcriptions) with 32K context, ~85-101x RTF on long audio, and a single-call ceiling around 30 minutes (no client-side chunking). Use when transcribing Chinese / English audio with StepFun, when long-form recordings (5-30 min) need to land in one request, when migrating from step-asr / step-asr-1.1, or when hitting the misleading model stepaudio-2.5-asr not supported error (which actually means wrong endpoint). Triggers on 阶跃 ASR, StepFun ASR, stepaudio-2.5-asr, 转录, 语音识别, 长音频转写, 语音转文字. For TTS with the sibling stepaudio-2.5-tts model, use the stepfun-tts skill instead.
An AWS Labs Model Context Protocol (MCP) server for valkey
Transforms raw meeting transcripts into high-fidelity, structured meeting minutes (notes / summaries). Use when (1) a meeting transcript is provided and meeting minutes, notes, or a summary are requested; (2) multiple versions of minutes must be merged without losing content; (3) existing minutes need review against the original transcript for missing items; (4) the transcript has anonymous speakers like "Speaker 1/2/3" or "发言人1" that need identifying (optionally mapped via a context.md team directory). Triggers on 会议纪要 / 会议记录 / 整理纪要 / 妙记转纪要, "write meeting minutes", "summarize this meeting", "merge these minutes", "what's missing from these notes". For fixing ASR/STT recognition errors in the raw transcript first, use transcript-fixer; this skill structures clean transcripts into minutes.
Transcribe audio/video to speaker-labeled text — who-said-what by default, plain-text opt-out; MLX-local on Apple Silicon or remote; local files, media URLs. Use for transcribing recordings/podcasts/lectures/meetings, ASR, speech-to-text, 转录, 语音转文字, 录音转文字, speaker diarization/说话人分离/识别/谁在说话, timestamps 字幕/时间戳/音画对齐, CAM++ voiceprint ID. This skill ALSO owns audio PREPROCESSING for ASR as a first-class trigger, even without transcription: convert any audio/video into an ASR-ready file (转换成适合 ASR 的格式, 转格式, convert/prepare audio for ASR, 音频预处理), downsample to 16kHz mono 16-bit (降采样, 重采样, 单声道, 归一化), merge multi-segment recorder dumps (多段合并/拼接, DJI TX01/TX02), transcode to small M4A + pitch-preserved speedup to cut metered-ASR billed minutes (转 M4A, 压缩上传, 加速, 1.3x, 飞书妙记/Feishu Minutes). Trigger even when it looks like a trivial one-line ffmpeg — the skill owns sample-rate/bit-depth/channel, merge-order, speed-vs-WER, format choices + a blessed prepareasrinput.py.
An AWS Labs Model Context Protocol (MCP) server for Timestream for InfluxDB
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.
Faithfully archive public WPS/KDocs/金山文档 links, especially embedded ProcessOn .pof mind maps and canvases, as raw source data, original SVG/PNG, and Markdown. Use when a user gives a kdocs.cn or wps.processon.com link and asks to scrape, save, download, 扒下来, 归档, or 转 Markdown without logging in or saving the document to an account.
An AWS Labs Model Context Protocol (MCP) server for AWS Step Functions
Diagnose Windows App (Microsoft Remote Desktop / Azure Virtual Desktop / W365 / direct PC) connection issues on macOS. Analyze transport protocol selection (UDP Shortpath vs WebSocket), detect VPN/proxy interference, parse Windows App logs for Shortpath failures, and resolve stuck "Configuring remote PC..." dialogs caused by expired Microsoft accounts, server reboots, or client-side auth poisoning. Use when VDI connections are slow or stuck, when direct PC connections fail to connect, when transport shows WebSocket instead of UDP, when RDP Shortpath fails, or when Windows App is frozen at a progress dialog.
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.
An AWS Labs Model Context Protocol (MCP) server for AWS Security Agent — automated security scanning, penetration testing, and remediation
Extract design systems from reference UI images and generate implementation-ready UI design prompts. Use when users provide UI screenshots/mockups and want to create consistent designs, generate design systems, or build MVP UIs matching reference aesthetics.
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.
MCP server for AWS SageMaker AI
Diagnoses and fixes Tailscale x proxy/VPN tool conflicts (Shadowrocket, Clash, Surge, OrbStack/Docker) on macOS — route hijacking, proxy env vars, system proxy bypass, SSH ProxyCommand double-tunneling, VM/container proxy propagation, stalled macOS DNS. Use when Tailscale ping works but SSH/HTTP times out, browser returns 503 but curl works, git push fails with "failed to begin relaying via HTTP", Docker pull/build times out behind TUN/VPN, setting up Tailscale SSH to WSL or remote dev over Tailscale, ssh/curl/git hang ~60s resolving a hostname while nslookup is instant, ping to a resolver works but dig times out, ssh -vvv freezes at "debug2: resolving", raw probes impossibly fast under a TUN (nc -z 0.00s), all DIRECT-routed sites fail at once (TLS handshake EOF, UNKNOWNCERTIFICATEVERIFICATION_ERROR, proxy CONNECT 503) while proxied sites work — TUN DIRECT split-brain — or a Windows host TUN (v2rayN) black-holing the whole machine incl. WSL and Tailscale (event-log forensics prove which action fixed it).
Creates educational Teams channel posts for internal knowledge sharing about Claude Code features, tools, and best practices. Applies when writing posts, announcements, or documentation to teach colleagues effective Claude Code usage, announce new features, share productivity tips, or document lessons learned. Provides templates, writing guidelines, and structured approaches emphasizing concrete examples, underlying principles, and connections to best practices like context engineering. Activates for content involving Teams posts, channel announcements, feature documentation, or tip sharing.
An AWS Labs Model Context Protocol (MCP) server for awslabs.s3-tables-mcp-server
【DEPRECATED · 已废弃】本 skill 已于 2026-08-07 停止维护。对作者本机环境：其方法论 （First Law 用户原话优先 / ABCDEFG 叙事框架 / baoyu-slide-deck 委托协议 / 四层目录治理） 已整体并入 deck-creator（私有仓 daymade-skills-pro 的 Route A · narrative）， 装有 deck-creator 的环境不要调用本 skill。对外部用户：这是最终版本， 保留安装兼容，不再接收更新。将在后续大版本中物理移除。
Set up and send technical status notifications through WeCom (Enterprise WeChat) webhooks. Use this skill whenever the user needs to send notifications, alerts, backup completion reports, or status updates via WeCom; when they mention 企业微信, 企微机器人, webhook, or alerting; or when a message needs to be clear, unambiguous, and technically precise rather than vague or condescending.
MCP server for discovering and exploring AWS Registry of Open Data datasets
Install, troubleshoot, and use Scrapling CLI to extract HTML, Markdown, or text from webpages. Use this skill whenever the user mentions Scrapling, uv tool install scrapling, scrapling extract, WeChat/mp.weixin articles, browser-backed page fetching, or needs help deciding between static and dynamic extraction.
Extracts files from repomix-packed repositories, restoring original directory structures from XML/Markdown/JSON formats. Activates when users need to unmix repomix files, extract packed repositories, restore file structures from repomix output, or reverse the repomix packing process.
An AWS Labs Model Context Protocol (MCP) server for Redshift
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.
Configures and runs LLM evaluation using Promptfoo framework. Use when setting up prompt testing, creating evaluation configs (promptfooconfig.yaml), writing Python custom assertions, implementing llm-rubric for LLM-as-judge, or managing few-shot examples in prompts. Triggers on keywords like "promptfoo", "eval", "LLM evaluation", "prompt testing", or "model comparison".
MCP server for interacting with AWS Managed Prometheus
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.
Multi-path parallel product analysis with cross-model test-time compute scaling. Spawns parallel agents (Claude Code agent teams + Codex CLI) to explore product from multiple perspectives, then synthesizes findings into actionable optimization plans. Can invoke competitors-analysis for competitive benchmarking. Use when "product audit", "self-review", "发布前审查", "产品分析", "analyze our product", "UX audit", or "信息架构审计".
An AWS Labs Model Context Protocol (MCP) server for postgres
Switch or repair the model configuration of an OpenClaw instance (e.g. Kimi k2p6 → k3): change the default model, add model definitions, and fix model-config failures — 401 "Invalid token", "No available channel / model not found", thinking-level rejections ("Thinking level X is not supported"), and config edits that don't take effect. Use whenever the user wants to switch/upgrade/rollback the OpenClaw model (切换模型/换模型/ 升级模型), or says the OpenClaw/龙虾 bot's model is misconfigured (模型配的错了), or the bot falls back / errors on LLM calls.
Send a single one-off message to a WeCom (Enterprise WeChat) group bot. Use this skill whenever the user says "/notify-wecom", "send a quick WeCom message", "企微通知一下", "临时发一条企业微信", or any one-shot notification that does not need a reusable template or setup workflow. The message is sent immediately; no confirmation prompt is shown unless the message is empty or the webhook is not configured.
An AWS Labs Model Context Protocol (MCP) server for Oracle Database on AWS RDS
Run a full 6-dimension health check of this Claude Code skills marketplace repo — code/script safety, documentation/SSOT consistency, security/PII leaks, open-PR triage, open-issue triage, and marketplace-manifest integrity — via a parallel fan-out Dynamic Workflow, then verify the serious findings and report them by priority. Use this whenever the user asks to check the repo, run a health check, do a full sweep/audit before a release, 全面体检, 检查仓库状态, 看看仓库健康吗, 审计一下仓库, or asks whether the PRs / issues / docs / versions / PII are in good shape across the board — even if they never say the word "workflow". Reach for it for any broad "is this whole repo OK" request, not just one-file checks.
Analyze and reclaim macOS disk space through intelligent cleanup recommendations. This skill should be used when users report disk space issues, need to clean up their Mac, or want to understand what's consuming storage. Focus on safe, interactive analysis with user confirmation before any deletions.
An AWS Labs Model Context Protocol (MCP) server for mysql
Launch and manage OpenAI Codex CLI (local agent) as a non-interactive coding sub-agent. Use when the user wants to delegate coding tasks to Codex, run code reviews, generate or refactor code, or use Codex GPT-5.5 agent capabilities through local CLI. Triggers on phrases like 'codex', 'run codex', 'codex exec', 'code review with codex', 'delegate to codex', 'use codex for coding', or any request to invoke the local Codex CLI agent. Uses ChatGPT Pro OAuth (flat-rate, no API charges) via ~/.codex/auth.json. Never uses API keys.
Co-create a personal investment-research LLM Wiki (Andrej Karpathy's pattern) where the user's OWN analysis framework becomes a living CLAUDE.md — by interviewing them, NOT by handing them a template. Use whenever the user wants to build a compounding research knowledge base, 投研第二大脑, 投研知识库, or 个人投研 wiki; instantiate Karpathy's LLM Wiki gist for finance/investing; turn their stock-picking, analyst-tracking, or earnings-watching workflow into a structured markdown vault; or build a wiki tracking companies / industries / macro / analysts over time. Pure markdown + wikilinks, NO RAG / vector DB (Karpathy's core idea — do not over-engineer). Also triggers for ingesting research reports / earnings calls / expert notes into an existing wiki, and for post-earnings prediction→fulfillment reviews. Core value = extracting the user's personal investment preferences into THEIR OWN schema, never imposing a standard one.
An AWS Labs Model Context Protocol (MCP) server for Microsoft SQL Server on AWS RDS
Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download brand logos for AI models/providers/applications (Claude, GPT, Gemini, etc.), or request icons in SVG/PNG/WEBP formats.
Reviews or re-reviews one contributor pull request—including an explicitly named closed PR being reconsidered—or a bounded newest-to-oldest sweep of all open contributor PRs, for a GitHub repository maintainer against the current base branch. Handles base drift, history discontinuities, polluted branches, ownership, curation, supersession, and review-conditioned repair or landing using immutable Git snapshots, three-way merge results, isolated contribution projection, checks, tests, and findings-first reporting. Use for a PR URL or number, "main changed, review again", "review all open PRs newest to oldest", "apply our maintainer principles", "can we merge this and fix the rest ourselves?", or merge readiness. Do not use for general GitHub CRUD, repository-wide audits, CI-only diagnosis, security-only diff audits, unpushed local diffs, merely addressing existing review comments, or merging without a fresh review.
An AWS Labs Model Context Protocol (MCP) server for Amazon ElastiCache Memcached
Audits, preserves, recovers, and safely retires local Git state: unpushed or wrong-branch commits, dirty or detached worktrees, forgotten duplicate clones of the same repo, untracked work no bundle can back up, orphaned stashes, dangling commits, stale branches, and squash/rebase merge uncertainty. Use when the user fears work was lost; asks to recover a commit or branch; asks whether a worktree, clone, or scratch directory can be deleted; wants everything converged onto one main branch; or needs proof that cleanup will not drop work. Use it even after an audit reported clean — the usual gap is scope: every in-repo command is blind to a second clone elsewhere on disk. Triggers on "did I lose work", "is everything merged", "is anything else lost", "safe to delete this clone", "clean up old branches/stashes", "only keep one main branch", "git reflog", "dangling commits", "分支灾难", "误删分支/commit", "worktree 能删吗", "还有没有丢的东西", "只保留一个主分支". Covers local-Git forensics, not GitHub PR/API operations or routine sync.
An AWS Labs Model Context Protocol (MCP) server for AWS Lambda Tools
An AWS Labs Model Context Protocol (MCP) server for managing AWS IAM resources including users, roles, policies, and permissions