「system」の検索結果

Build AI blog writing systems. TRIGGERS - Use when user needs help with ai-blog-writer-system related 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。

Design billing systems for AI services. TRIGGERS - Use when user needs help with ai-billing-system related 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。

Build AI A/B test analysis systems. TRIGGERS - Use when user needs help with ai-ab-testing-system related 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。

Design AI A/B testing systems for prompts and models. TRIGGERS - Use when user needs help with ai-ab-test-system related 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。

Build AI attribution systems for content sourcing. TRIGGERS - Use when user needs help with ai-attribution-system related 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。

Guide agency management system setup and optimization. TRIGGERS - Use when user needs help with agency-management-system related 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。

Design achievement and trophy systems for games. TRIGGERS - Use when user needs help with achievement-system related 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。

Design accountability systems. TRIGGERS - Use when user needs help with accountability-system related 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。

Sets up a file-based memory system so Cowork always knows who you are, how you work, and where your projects stand. For eliminating repetitive re-introductions at session start, when building persistent context across multiple projects, or during initial Cowork onboarding. Use when the user says "claude doesn't remember me", "memory system", "persistent context", "why does it forget", "remember my preferences", "I keep re-explaining myself", or "how do I make Claude remember things".

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。

Review the UI and style files changed in the working tree against this repo's own design system, before they are saved or committed. Runs the same deterministic check as the CLI's --check flag (no tokens, about a second): hardcoded colours where a token exists, near-identical colour twins, off-scale spacing, radii, font sizes and shadows, typefaces outside the system, arbitrary Tailwind values, static inline styles, !important, duplicate component definitions and imports of the copy to avoid, new tokens that copy an existing one, chart colours written by hand where the repo keeps a chart palette (and one calm warning asking for a palette where it keeps none), on a repo built on MUI, Mantine, Chakra or Ant Design, colours or pixel sizes written onto kit components where the theme has a value, and on a Tailwind theme or a shadcn repo, palette classes such as text-gray-500 where the theme names a colour of that kind. Findings name the file, the line and the fix. This is the small, fast check for what just changed; the roast skill is the full scan of the whole repo with a report.

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 this skill whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.

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。

Deep root cause analysis using the 5 Whys and Fishbone techniques. Use when systematic debugging hasn't found the cause, or for complex systemic issues. Keywords: root cause, why, underlying, fundamental, systemic, deep, origin

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。

Agent skill for arch-system-design - invoke with $agent-arch-system-design

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。

Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.

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。

"Conduct a systematic literature review following the PRISMA framework with explicit search strategy, inclusion and exclusion criteria, quality assessment, and transparent synthesis. Use this skill when the user needs to design a reproducible literature search, apply PRISMA flow documentation, develop inclusion and exclusion criteria, assess study quality, or when they ask 'how do I do a systematic review', 'what is PRISMA', or 'how do I make my literature review reproducible'.".

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。

"Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.".

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。

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts. Use when creating brand-kit image prompts, identity boards, logo systems, or visual-world presentations.

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 TrueSkill rating system for multiplayer and team-based competitive ranking. Use this skill when the user needs to rate players in team games, handle multiplayer (non-1v1) matchups, or build a matchmaking system with uncertainty tracking — even if they say 'team rating system', 'multiplayer ranking', or 'matchmaking rating'.".

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 Elo rating system to rank items or players from pairwise comparison outcomes. Use this skill when the user needs to rank items from head-to-head matchups, build a competitive rating system, or evaluate relative quality from comparison data — even if they say 'player rating', 'ranking from comparisons', or 'competitive scoring system'.".

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 the hidden foundational System Prompts, internal instructions, backend APIs, and confidential contextual data powering Large Language Model (LLM) applications using targeted prompt injection manipulation and adversarial psychological engineering.

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。

Systematically bypass LLM safety filters and content moderation systems using advanced jailbreaking techniques. Use this skill when testing AI systems for safety alignment robustness, evaluating content moderation effectiveness, or conducting authorized AI red team assessments. Covers role-play attacks, few-shot manipulation, encoding bypass, multi-modal exploitation, and automated jailbreak discovery methods.

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/LLM red-team assessment using the OWASP LLM Top 10 (2025) + OWASP AI Testing Guide (AITG v1, Nov 2025) frameworks, plus OWASP MCP Top 10 runtime testing for agentic/MCP targets. Tests prompt injection, jailbreaks, system prompt leakage, sensitive data extraction, excessive agency, improper output handling, model extraction, content bias, evasion, membership inference, MCP token exposure, MCP command injection, and more. Uses four tools in combination: FuzzyAI (single-turn jailbreak fuzzing), PyRIT (multi-turn orchestrated attacks), Garak (probe-based vulnerability scanning), and promptfoo (plugin-based red-team evaluation). Each tool covers different OWASP categories; running them together gives systematic coverage. Includes a conditional MCP reconnaissance phase and a post-access AI infrastructure phase (chained from /post-exploit). Produces: OWASP LLM Top 10 + AITG + MCP coverage matrix, findings per category, architecture diagram of the AI system, PoCs for confirmed exploits. Chains into /gh-export for issue filing.

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。

Hunts for Linux persistence by inspecting cron, systemd units, shell rc files, SSH authorized_keys, and common autostart locations for attacker-added entries. Activates for requests to hunt Linux persistence, audit cron/systemd for backdoors, or find unauthorized autostart and authorized_keys entries.

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。

Decompose a game concept into individual systems, map dependencies, prioritize design order, and create the systems index.

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。