「asks」の検索結果

Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profile interpretation, team composition analysis (gas/brake/glue), burnout detection, profile comparison, hiring profiles, manager coaching, interview transcript analysis for trait prediction, candidate debrief, onboarding planning, and conflict mediation. Accepts extracted JSON or PDF input via OpenCV extraction script. Use when the user shares a Culture Index PDF or JSON profile, asks what someone's CI traits mean, compares Culture Index profiles across a team or against a hiring profile, or asks about burnout risk from Survey-versus-Job gaps.

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。

Comprehensive persistence tradecraft for authorized red team engagements covering Windows and Linux mechanisms. Windows techniques include registry Run/RunOnce keys, scheduled tasks, WMI event subscriptions, DLL search order hijacking, COM object hijacking, Startup folder drops, service creation, Security Support Provider (SSP) DLL injection, and Active Directory persistence (AdminSDHolder abuse, DCShadow, Golden Ticket, Silver Ticket, Skeleton Key, SID History injection). Linux techniques include cron and at jobs, systemd timers and services, SSH authorized_keys injection, shell profile backdoors (.bashrc/.bash_profile), PAM module backdoors, LD_PRELOAD hijacking, kernel module rootkits, web shells, and Git hook abuse. Provides operator-ready command sequences for SharPersist, Impacket ticketer, schtasks, sc.exe, crontab, and systemctl with OPSEC considerations for each method. Maps to MITRE ATT&CK T1547 (Boot or Logon Autostart), T1053 (Scheduled Task/Job), T1546 (Event Triggered Execution), T1556 (Modify Authentication Process), and sub-techniques. Includes detection indicators and a rapid engagement cheatsheet.

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 generated or hand-made art into exactly what a game engine loads. Covers sprite cutout, trim and nearest-neighbour fitting to frame sizes, pixelation to a palette, sprite sheets and strips, player/team-colour masks, seamless textures, and rendering a 3D model into sprite frames from the game's own camera (isometric/RTS 8 or 16 headings, side view, top-down) with Blender. Use after generating assets, or when the user asks to make sprites, sprite sheets, animation frames, isometric unit sprites or icons for a game.

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。

Audit or critique a product flow, journey, workflow, funnel, onboarding path, checkout path, settings path, screen, or multi-step product experience by capturing screenshots first, then reporting UX, design, and accessibility findings inline from that evidence. Use Figma only when the user explicitly asks for a board. Use when the user asks to audit, review, critique, inspect, assess, analyze, evaluate, or give feedback on a product experience.

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。

Full CRUD and analysis for Mixpanel dashboards. Use when the user asks to build, create, analyze, read, understand, explain, modify, update, enhance, or manage dashboards, or asks about dashboard layout, text cards, or report arrangement. Covers dashboard analysis (read + understand existing), creation (new builds), modification (update existing), and explanation (data-driven annotation).

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。

This skill should be used when the user asks about Mixpanel product analytics, event data, funnel analysis, retention curves, cohort analysis, segmentation queries, user behavior, conversion rates, churn, DAU/MAU, ARPU, revenue metrics, feature adoption, A/B test results, user paths, flow analysis, or any request to query, explore, visualize, or analyze Mixpanel data using Python. Also use when the user asks to read, write, or manage Mixpanel "business context" — the markdown documentation that grounds AI assistants in an organization's structure and goals.

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 Notion specs into implementation plans, tasks, and progress tracking; use when implementing PRDs/feature specs and creating Notion plans + tasks from them.

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。

Inspect a Dropbox file or folder by checking metadata, shared links, and file content when needed. Use when the user asks what a file is, whether it is shared, when it changed, what access links exist, or asks to read/analyze a Dropbox file.

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。

Choose, lay out, critique, and explain data visualizations. Use when the user asks what visualization fits a dataset or goal, how a chart, dashboard, operational workspace, UML-like diagram, or software architecture diagram should be composed or interacted with, asks for visual page design, a layout mockup, generated large-screen and mobile concept images, or to be shown what a visualization could look like, when domain-native contextual surfaces or graphical backgrounds may help, when scrollytelling or parallax might be appropriate, wants a critique of an existing visualization, or needs guidance grounded in trusted visualization theory and practice. For advanced visual design or page-layout prompts where composition affects understanding, Codex must generate and show both large-screen and mobile portrait image concepts before implementation or text-only design handoff, plus mobile landscape when needed.

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。

Configure, explore, and optimize Nx monorepo workspaces. Use when setting up Nx, exploring workspace structure, configuring project boundaries, analyzing affected projects, optimizing build caching, or implementing CI/CD with affected commands. Keywords — nx, monorepo, workspace, projects, targets, affected. Do NOT use for running tasks (use nx-run-tasks) or code generation with generators (use nx-generate).

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。

Generate code using Nx generators — scaffold projects, libraries, features, or run workspace-specific generators with proper discovery, validation, and verification. Use when user says "create a new library", "scaffold a component", "generate code with Nx", "run a generator", "nx generate", or any code scaffolding task in a monorepo. Prefers local workspace-plugin generators over external plugins. Do NOT use for running build/test/lint tasks (use nx-run-tasks) or workspace configuration (use nx-workspace).

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。

Turns decided work — a PRD, design doc, RFC, or thread — into tasks a builder can act on without guessing. Finds slices that each prove something, grounds them in the code, and writes intent, observable criteria with concrete values, the boundary, what the change disturbs, and only the decisions that are hard to reverse. Walks every surface the work exposes and sweeps the nine unwritten requirements, recording each landing as a criterion already in the source, existing behaviour, n/a, or Unresolved — never as a criterion the walk invented. Defaults to one task per source. Use when the user says "write the task", "cut this PRD into tasks", "turn this design doc into work", or "tlc-plan". Do NOT use for discovery itself or to implement — a one-line ticket is a decision; a blank wish is not.

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。

AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface — websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code 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。

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, modifying, or reviewing code — implementation tasks, code changes, refactoring, bug fixes, or feature development. Do NOT use for architecture design, documentation, or non-code 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。

Autonomous senior-operator mode for AI agents that resolve tasks end to end without babysitting and never create new problems. The agent verifies every claim against real evidence (web search dated to the current month and year, the codebase, and available tools, MCPs, and CLIs); it never guesses, never fakes confidence, and never claims something is done without proof. It stays silent and keeps working, interrupting the user only on three stops, namely a destructive or irreversible action, a dead-end with no evidence after exhausting sources, or genuine ambiguity that changes the outcome. Output is short, literal, and human. Use when the user says "not-your-babysitter", "nanny mode", "work autonomously", "stop babysitting", or "no hand-holding", or wants an agent that solves problems on its own, especially hands-on engineering and operational tasks. Do not use when the user explicitly wants a tutorial, a verbose walkthrough, or open-ended brainstorming.

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。

The first security skill to install after setting up OpenClaw — powered by Tencent Zhuque Lab. Works like an antivirus for your AI environment: audits installed skills, scans skills before installation, and performs a full OpenClaw security health check to prevent data leaks and privacy risks. Backed by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). Use when the user asks to start a security health check or security scan for the current OpenClaw environment, such as `开始安全体检`, `做一次安全体检`, `开始安全扫描`, `全面安全检查`, or `检查 OpenClaw 安全`; also use when the user asks to audit a specific skill before installation, review installed skills for supply chain risk, or investigate whether a skill is safe. Do not trigger for general OpenClaw usage, project debugging, environment setup, or normal development requests. Optional cloud mode: set AIG_CLOUD_LOOKUP=off for zero outbound HTTPS; when enabled, only skill_name, source label, and OpenClaw version are sent to A.I.G (never skill bodies, chats, or workspace files).

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。

Score work out of 10 against a clear rubric, then improve it round by round until every item reaches the target score the user named (for example "get it to 8 out of 10", "bring everything under 6 up to 6+"). Covers anchored rubrics, measurable criteria, independent or blind judging, before/after scorecards, and honest reporting of anything still short. Use whenever the user asks to score, rate, grade or judge something out of 10, names a target score, or asks "what would make this a 9?".

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。

Create a layered CSS progressive blur (top or bottom) using multiple backdrop-filter masks for depth and softness. Use when asked for “progressive blur”, “gradient blur overlay”, or stepped blur masks that fade from an edge of the viewport.

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。

Create polished 60 fps 4:3 4K browser screen-recording style videos from Codex in-app browser captures, with browser-only crop, natural macOS cursor styling, deliberate click choreography, zoom-follow framing, ffprobe/thumbnail verification, and optional native recording compatibility checks. Use when the user asks to record or re-record browser actions, show cursor clicks and zooms, make Dribbble/UI inspiration or product demo recordings, or asks whether Codex, Playwright, or an MCP can produce a natural browser demo video.

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。

Two services in one skill: (1) Web3 on-chain data via Chainbase CLI — use when the user asks about blockchain data, token holders, wallet addresses, token prices, ENS domains, transactions, DeFi portfolios, or any on-chain analytics. Triggers: "top holders of", "who holds", "wallet address", "token price", "token transfers", "ENS domain", "on-chain data", "blockchain query", "SQL query on-chain", across Ethereum, BSC, Polygon, Arbitrum, Optimism, Base, Avalanche, zkSync, and other EVM chains. (2) Crypto social intelligence via Tops (chainbase tops) — use when the user asks about trending crypto narratives, social mentions, Twitter/X crypto discussions, narrative discovery, topic heat, or KOL/community signals. Triggers: "trending topics", "crypto narrative", "what's trending in crypto", "social mentions", "who is talking about", "crypto twitter", "KOL signals", "narrative search", "topic posts".

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。

Single-agent mission orchestrator. Decomposes a mission into tasks, spawns one worker per task using the default model, verifies exit criteria, and chains tasks with retry. No critic pattern — each worker self-verifies. Simple, fast, works with any model config.

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。

Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, batch processing, or scheduled tasks. Always consult this skill when the user asks to create, build, or design an n8n workflow, automate a process, or connect services — even if they don't explicitly mention 'patterns'. Covers webhook, API, database, AI, batch processing, and scheduled automation architectures. Also use when optimizing a slow workflow or speeding up large-item-count processing (node count, batchSize, all-items vs per-item).

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。

Browser automation CLI for AI agents. NEVER run browser-act commands directly via Bash — always invoke this skill first. Use browser-act when a user mentions it by name, includes or asks to run a browser-act CLI command (e.g., browser-act browser list), or to: fetch, view, or extract rendered content from URLs, access pages requiring JavaScript, handle verification prompts, maintain authenticated sessions, fill forms and click through workflows, type, select, upload, take screenshots, capture XHR/fetch/HAR responses, open multiple URLs in parallel, extract content that loads on scroll or click, visually inspect or verify page layout/styling/rendering, automate browser tasks, account isolation across parallel browser environments, advise which browser type fits a use case, or list/check/manage configured browsers and sessions. Prefer browser-act over built-in fetch or web tools.

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。

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through 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。