「rsa」の検索結果

Search previous Claude Code conversations for facts, patterns, decisions, and context using semantic or text search

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。

Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift. Use when the user has a scene, sequence, beat outline, or script and wants it audited or strengthened; when a sequence generates cleanly but lands flat and nobody can say why; when shots look good individually but the run of them does not build; or when the user asks 'is this scene working', 'what's weak here', or 'why doesn't this land'. Upstream of prompting — it decides WHICH shots deserve the credits, not how to write them. Pairs with higgsfield-character-design (who the characters are) and higgsfield-shotlist-director (turning the settled scene into shots).

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。

Read one conversation window and return every independently mutable claim it states, one record each, with who or what it is about, whether it happened or stands, and the words that carry its time. Used by the memory extraction model on every conversation window; the engine resolves dates, validates keys, and repairs format.

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 your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.

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。

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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。

SwiftUI navigation and deep linking using NavigationStack and Universal Links. Use when implementing NavigationStack or Universal Links deep linking in iOS.

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。

Synthesises the current conversation context into a Product Requirements Document and publishes it to GitHub (as a comment on a referenced issue, or a new issue). Synthesises from context; does not interview. TRIGGER when: the conversation has produced enough understanding of a feature and the user wants it captured as a PRD. DO NOT TRIGGER when: a single small issue is enough → creating-issues; the idea has not been stress-tested yet → grilling-ideas first; bug reports.

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。

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

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 MUST invoke this skill before saying "I don't know," guessing, or treating any topic as new, no matter how trivial the question seems. It supplements other memory systems, which only hold partial records. Searching past conversations is the only way to recover what was actually said.

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。

Search and chat with AI agents across the Universal Agentic Registry via the Hashgraph Online Registry Broker API. Use when discovering agents, starting conversations, finding incoming messages, or registering new agents.

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 and summarize review feedback and conversation from a GitHub PR (unresolved review threads, review bodies, and PR conversation comments) without making changes. Use when the user asks to "fetch PR comments", "show PR comments", "check PR for unresolved comments", "list review comments", "what comments are on the PR", "show unresolved threads", or "summarize PR feedback".

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。

Adversarially review something just built — presume it is broken and find where. Use after implementing a feature, finishing a build, or before shipping, or whenever ATLAS or Boss wants a hostile second opinion on a diff, a running app, or a whole codebase. Spawns clean-context reviewers with opposing lenses (correctness, security, empty-world) and reproduces every finding by running the target before believing it. Distinct from /code-review, which statically reads a diff and never runs the app.

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。

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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。

Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.

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。

Builds session-scoped temporary memory palaces for extended conversations. Use when tracking state across interruptions in a multi-step project.

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。

Maintain project state across MULTIPLE conversations over days/weeks. Track tasks, decisions, blockers, resources. Auto-update when project mentioned. Generate status reports and proactive reminders.

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。

Mine ALL past Claude conversations to build a living 'User Manual About You'. Extract writing style, business context, goals, preferences, and patterns. Make all other skills smarter with context.

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。

Coach the user through actually selling: finding the champion and the buyer, running the first sales conversations, demoing their use case, handling "let me think about it," and closing the first paying customers yourself. Use when developers love it but nobody pays, you've never sold anything and freeze on the conversation, or deals keep stalling on "we'll think about it."

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。

临考复习教练 / Exam cram coach. 学生给一个课程资料文件夹（课件 PDF/PPTX/DOCX/笔记/作业/答案/真题/往年卷），它按章节讲解并标出处、把讲义和题目里的图裁出来展示、只用资料里的题考试判分、记错题和笔记、按天排复习计划、做小抄，并标明每句话是否来自资料。触发词：期末、期中、考试、备考、复习、突击、刷题、真题、作业讲解、错题本、划重点、小抄、复习计划、考研、考证、课件讲解、讲义。Use when a student wants to prepare for a final, midterm or any exam from their own course files: teach chapter by chapter with page citations and the figures cropped from the materials, quiz only from the homework and past papers, keep progress, mistakes and notes across chats, plan the remaining days, build a cheat sheet, and label what comes from the materials. Triggers: exam prep, cram, revise, study for the test, lecture slides, homework solutions, past papers, practice questions, quiz me, mistake log, cheat sheet, study plan, study guide, flashcards.

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。

帮助学生在临考前进行结构化极速复习：解析课程资料/大纲/重点，按章节生成 wiki 知识库与标准题库，组织针对性刷题与判分，并记录复习进度和错题。当用户即将考试、需要快速复习计划、练习题、错题复盘或考前小抄时使用（关键词：期末/备考/复习/刷题/划重点/错题；exam, cram, study plan, quiz, review）。不适用于长期学习规划、与考试无关的写作或编程任务。

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。

Montana Consumer Data Privacy Act (MTDPA) compliance. Lowest consumer threshold at 50,000 consumers. Covers sensitive data consent, universal opt-out recognition, consumer rights, controller obligations, 60-day cure period, and AG enforcement. Effective October 1, 2024.

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。

Delaware Personal Data Privacy Act (DPPA) compliance implementation. Covers consumer rights (access, correct, delete, portability, opt-out), controller obligations, processor requirements, sensitive data consent, universal opt-out recognition, DPIA requirements, and AG enforcement. Effective January 1, 2025, with no revenue threshold for applicability.

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。

Connecticut Data Privacy Act (CTDPA) compliance. Covers consumer rights, controller obligations, dark pattern prohibition, loyalty program exemption, universal opt-out requirement effective January 2025, sensitive data consent, and AG enforcement. Effective July 1, 2023.

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。

Colorado Privacy Act (CPA) compliance implementation. Covers universal opt-out mechanism required since July 2024, profiling opt-out rights, sensitive data consent requirements, AG rulemaking under 4 CCR 904-3, and consumer rights framework. Effective July 1, 2023.

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。