934 件 ・ 関連度順
概要と使いどころ
Collect this machine's local Claude Code conversation data with the asz collector. Resolves the local Claude data directory (honouring CLAUDE_CONFIG_DIR and XDG_CONFIG_HOME), builds the binary, lists what is discoverable, and lands everything into the storage root. Use when asked to collect, backfill, re-collect, or inspect local Claude Code sessions, or to check what the collector can see.
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。
4-layer recall procedure (durable → semantic → PostgreSQL → daily notes) before claiming "no context". Invoke when user explicitly asks "do you remember", "what did we discuss about X", "search history". NOT a general assistant — only fires when recall is the explicit task. Drop the prior "use proactively" rule. Triggers: "do you remember", "what did we discuss", "when did", "find that conversation about".
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。
Know when NOT to speak in group chats. Use this skill before replying in any group conversation to decide if a response adds unique value or is just noise. Prevents unsolicited jumping-in, echo responses, and unnecessary acknowledgments.
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。
Session stores conversation history for a specific session, allowing agents to maintain context without requiring explicit manual memory management.
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。
NotebookLM MCP server management - query notebooks, add from share links, handle auth, reset sessions. Use when working with Google NotebookLM notebooks for conversational research tasks.
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。
Compact the current conversation into a handoff document for another agent to pick up.
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。
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
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。
Reads Copilot conversation history and extracts executive-ready success stories. Use when the user asks to study prior Copilot sessions, summarize what was done before, mine evidence, or quantify time, cost, risk, and priority alignment from GitHub Copilot history in any workspace or repository.
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。
Enforces lean, surgical output. Suppresses conversational fluff and verbose reasoning traces. Use when agent output feels too chatty or repetitive.
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。
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
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 deep scan and ingest project files (.md, .json, agent.md, .openwiki) and past conversation logs into the local memB vector memory engine.
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 or improve a job seeker's resume.md source file from conversational career input. Use when the user wants to create resume.md, organize new-grad or experienced career history, convert raw experiences into STAR/CAR evidence, add missing metrics, or prepare reusable career evidence for cover letters and job applications. 한국어 요청도 포함합니다 - 이력서 작성, 이력서 정리, 경력기술서, 경력 정리, 커리어 정리, 자소서 소재 정리, 내 경험 정리해줘, 신입 이력서, 경력직 이력서.
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。
Guide for dataset construction — SupervisedDatasetBuilder, RLDatasetBuilder, ChatDatasetBuilder, and custom dataset creation from JSONL, HuggingFace, or conversation data. Use when the user asks about datasets, data loading, data preparation, or custom data formats.
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。
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
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。
Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket.
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 user has ADHD or attention differences — tracks current task, catches conversation drift, and nudges back on topic without judgment or guilt.
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。
Unified chat inbox (Busabase App-in-Skill) aggregating WhatsApp, Discord, Slack, and Telegram messages into one place with a reply queue. Use when the user invokes $kelly-messenger or /kelly-messenger, wants a unified inbox, chat aggregation, to read WhatsApp/Discord/Slack/Telegram messages in one place, review unanswered conversations, queue or approve replies, run connector sync, or manage the outgoing reply queue.
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 a URL and save the body to a temp file so you can pipe it through rg / jq / awk instead of dumping the whole page into the conversation. Use this whenever a user gives you a URL to read - articles, docs, PRs, gists, README files, blog posts, anything HTTP. Returns a path on disk; the agent then greps the path for the relevant section and quotes only what matters. Strongly preferred over the built-in webfetch tool when (a) the page is more than a few KB, (b) the user wants to find a specific phrase / table / code block on the page, (c) you need to keep the long page out of context, or (d) you want to inspect raw HTML alongside rendered markdown. Triggers: 'fetch', 'fetch this URL', 'fetch and save', 'fetch the page', 'pull this', 'grab this article', 'read this URL', 'read the docs at', 'mirror this page', 'page is too long', 'save the page so I can grep it', 'put it on disk so I can rg', 'cache this URL'.
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。
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
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。
Transforms conversations and discussions into structured documentation pages in Notion. Captures insights, decisions, and knowledge from chat context, formats appropriately, and saves to wikis or databases with proper organization and linking for easy discovery.
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。
Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
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。
Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.
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。
Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
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。
Automatically persist useful context — research, decisions, learnings, templates — to workspace files so knowledge survives across conversations.
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。