'preferences' 검색 결과

Set up Diverga through an interactive researcher profile wizard. It records your discipline, experience, statistical tools, database access, and collaboration preferences, then saves configuration that guides explanations, code suggestions, and database recommendations.

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• Setting up a Diverga researcher profile
• Updating statistical software preferences
• Recording available academic databases

Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.

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• Add conversation history to a chat system
• Remember user preferences across sessions
• Reuse patterns from successful interactions

Build an initial account profile from public social media content and guided questions. Organize positioning, style, audience, platforms, preferences, and initial insights into six files, marking where information came from and what still needs clarification.

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• Creating an account profile for the first time
• Reviewing positioning and style from existing posts
• Organizing content preferences and boundaries

Check draft content against an existing creator Profile covering account focus, audience, formats, tone, and preferences. Receive consistency scores, evidence of mismatches, and specific editing suggestions, while keeping publication decisions with the user.

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• Check whether a draft matches the account's focus
• Review tone and wording against a defined style
• Check alignment with the intended audience

Build two to four audience profile cards from follower characteristics, needs, content preferences, and channel information. Use account data, comments, and messages to guide content choices, prioritize outreach channels, and plan how to validate the profiles.

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• Define who an account's content should serve
• Organize follower concerns from comments and messages
• Plan content around audience preferences

Update user profile information when user shares preferences, habits, or work details. When you need to save user preferences, remember user's work domain, or provide personalized service.

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Record important information to long-term memory for learning user preferences, successful patterns, and error lessons. When you need to remember user preferences, save successful patterns, or record lessons from errors.

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Local user-profile maintenance skill for Codex, Claude Code, OpenClaw, OpenCode, and other agent harnesses. Use only when the user explicitly invokes $user-profile-keeper to create, initialize, update, query, correct, delete, export, or audit a local persistent user profile. It can extract durable collaboration preferences, requirement-expression habits, capability boundaries, recurring omissions, risk preferences, privacy boundaries, and typical events from the current session into auditable, confirmable, retractable local profile data. Do not auto-invoke, upload profile data, or replace task-clarifier's normal clarification flow.

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Customise the prd-taskmaster plugin workflow via curated brainstorm questions. The AI asks, the user answers in plain English, and the skill writes their preferences to .atlas-ai/config/atlas.json. Future runs of prd-taskmaster read that file and apply user preferences to phase gates, validation strictness, default provider, preferred execution mode, and template choice. For deeper tweaks beyond the curated questions, users can hand-edit files in .atlas-ai/customizations/. Use when the user says "customise workflow", "customize workflow", "adjust my PRD settings", "tune the skill", or wants to change how prd-taskmaster behaves.

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.omd/preferences.md의 status:pending 항목을 Core v2 System Graph에 합쳐 DESIGN.md를 재생성하고 status를 applied로 플립. '프리퍼런스 정리해줘', 'fold preferences', 'apply all corrections', 「好みをDESIGN.mdに反映」, 「套用偏好」류의 요청에 트리거. 단발성 교정 기록은 omd:remember.

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시스템이 학습한 사용자의 디자인 취향을 한 뷰로 렌더. .omd/preferences.md + foldin-proposal.json + DESIGN.md를 읽어 반영됨/대기 중/보류됨/모르는 것 4그룹으로 보여준다. '/omd-taste', '내 취향 보여줘', '취향 현황', 'what are my preferences', 'show my taste', 「私の好みを見せて」, 「顯示我的偏好」류의 발화에 트리거. 기록은 omd:remember, DESIGN.md 반영은 omd:learn.

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Analyzes conversation transcripts to extract user corrections, patterns, and preferences, then proposes skill improvements. Use this skill when users provide corrections, express preferences about code style, or when patterns emerge from successful approaches. Can be triggered manually with /reflect or automatically at session end when enabled.

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Extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs. Use when asked to learn preferences, mine feedback, personalize workflows, or generate team/person-specific agent guidance.

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Audience Analysis workflow skill. Use this skill when the user needs Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Audience Analysis workflow skill. Use this skill when the user needs Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Cross-cutting: what AutoCode remembers and how every session starts. Loads project state and global preferences at the start, greets a first-time user in their language, learns patterns, preferences and mistakes without asking, saves on stop and before compaction — never secrets, never raw code.

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Generate or redesign evidence-based README files for apps, libraries, CLIs, monorepos, and agent skills. This skill should be used for /readme-write, /readme, generate readme, write readme, improve readme, 帮我写 README, 美化 README, README を書いて, README 작성해 줘, напиши README, or their equivalents in any language. Confirm reader and visual preferences before generation; every README includes a source-backed flowchart, and every language edition keeps identical content apart from the language. Git-driven updates are routed to the companion readme-update skill.

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Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.

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Detects sensitive data stored insecurely on mobile devices (Android/iOS). Trigger on: SharedPreferences, NSUserDefaults, SQLite, Room DB, DataStore, Core Data, Keychain misconfiguration, external storage, backup exposure, plaintext files, unencrypted databases, adb backup, iCloud backup, NSFileProtection, EncryptedSharedPreferences, SQLCipher, allowBackup, FLAG_SECURE, keyboard cache, sensitive logs. Covers MASVS-STORAGE-1 (local storage) and MASVS-STORAGE-2 (exposure to unauthorized actors).

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User ryzen's workflow preferences, communication style, and anti-patterns to avoid

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Load this skill whenever the project has personalization features, user preference controls, theme selectors, font size adjusters, motion toggles, contrast settings, or any user-configurable accessibility accommodations. Under no circumstances override or ignore user OS-level accessibility preferences without explicit user consent. Absolutely always persist user preferences, apply them immediately, and respect prefers-reduced-motion, prefers-contrast, and similar media queries.

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FlutterSecureStorage (v10.x) for encrypted key-value storage of sensitive data using platform-native secure enclaves with biometric authentication support. Use this skill when storing OAuth tokens (access tokens, refresh tokens, ID tokens), API keys and secrets, user passwords or PINs, session tokens, encryption keys, private keys for cryptography, certificate data, biometric enrollment data, banking credentials, health data, or any sensitive information requiring platform-level encryption (iOS Keychain with Secure Enclave, Android Keystore with Hardware-backed keys). Supports Touch ID, Face ID, and Android biometric prompt integration. Handles biometric change invalidation (resetOnError), data migration from SharedPreferences/EncryptedSharedPreferences, Google Drive backup exclusion, automatic key rotation, configurable encryption algorithms (AES), and prevents data extraction even on rooted/jailbroken devices. Essential for authentication flows, secure credential management, or compliance requirements (PCI DSS, HIPAA, GDPR data protection).

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Android アプリ開発 (Kotlin) のデータ層リファレンス。Jetpack androidx。 Room / Room 3 (androidx.room3) (Entity, Dao, Query, Migration, prepopulate, createFromAsset), DataStore (Preferences/Proto, Direct Boot), MediaStore, SharedPreferences, スコープ付きストレージ, Retrofit, OkHttp。

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Turn vague preferences about employers into criteria that can actually be used to choose between them: for each one, what would have to be seen to confirm it, whether it comes from firsthand experience or from an untested assumption, whether it is a must, a nice-to-have, or something to avoid, and which pairs of criteria pull against each other while both being treated as required, then test the set against real candidates. Use when a new graduate is working out what to select employers on, when someone who has decided to move needs criteria for where to apply, or when a stated axis like "a place I can grow" needs to be made checkable; do not use to recommend an industry, job, or employer, to score or rank candidates, or to judge someone's stated preferences.

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