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概要と使いどころ
Execute sophisticated Prompt Injection and Jailbreak techniques against Large Language Models (LLMs) to bypass safety filters, extract system prompts, and manipulate the AI's output to perform malicious or disallowed actions.
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Exploit Active Directory environments using Pass-the-Hash (PtH). This skill details how to authenticate to remote systems using the NTLM hash of a user's password instead of the plaintext password, enabling lateral movement and privilege escalation without cracking hashes.
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Execute a Kerberoasting attack to extract and systematically crack the NTLM hashes of Service Principal Name (SPN) accounts in an Active Directory environment. Uses tools like Rubeus, Impacket (GetUserSPNs), and Hashcat to achieve domain privilege escalation domain: cybersecurity
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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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。
Append a session/state snapshot to MEMORY.md (regardless of where it lives — for this repo it's `founder/MEMORY.md`). Use when the user says "snapshot memory", "save state to memory", "/memory-snapshot", "log what happened in MEMORY", or otherwise asks to record the current session's outcomes for the next orchestrator. Locates the project's MEMORY.md, prepends a dated entry above the previous snapshot (newest first), preserves every existing entry (NEVER overwrites or truncates), and reports back the file path + byte delta. Not for one-off feedback memories (use the user-level memory system at ~/.claude/.../memory/ for those). Not for trimming or deleting old 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。
Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a 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。
Market franchise systems — franchisee recruitment, local-national marketing balance, and brand consistency at scale.
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。
Organize files so you can find anything: naming conventions, folder structures, archiving, and deduplication. Use when digital clutter slows you down or you're setting up a new 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。
Reach and sustain inbox zero: triage workflows, filters, templates, batching, and unsubscribing systems. Use when email eats your day or your inbox has become an anxiety source.
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。
Master professional email — inbox zero systems, high-impact writing, etiquette, and managing email at scale.
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。
Systematic drug repurposing — computational screening, evidence triangulation, and validation strategy.
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。
Manage CRM systems — data architecture, pipeline design, automation, user adoption, and reporting.
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。
Systematic contract review assistance — clause extraction, risk flagging, and comparison — use when analyzing agreements.
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。
Systematic debugging: reproduce, isolate, hypothesize, verify — with tooling for hard bugs. Use when stuck on a bug, flaky failure, or production incident.
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。
Manage ML datasets with the datasets ecosystem — loading, streaming, preprocessing, versioning, and sharing. Use when data handling (not modeling) is the bottleneck.
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。
Chaos engineering — designing safe failure-injection experiments to build resilience — use when proactively testing system robustness.
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。
Capacity planning — forecasting demand, sizing infrastructure, and avoiding both outages and waste — use when scaling systems.
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 complete brand identity systems with strategy, visual language, voice, and usage guidelines.
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 a bookmark system you'll actually use: capture, tagging, retrieval, and regular pruning. Use when bookmarks pile up unfindable or you keep losing useful links.
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。
Professional C: memory ownership, defensive programming, build hygiene, and systems-level correctness. Use when writing, reviewing, or maintaining C code.
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 conversational multi-agent systems with AutoGen — agent types, group chats, and orchestration patterns.
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 memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.
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 LLM applications with chain-style orchestration frameworks — prompts, chains, tool-calling agents, memory, and retrieval pipelines. Use when structuring multi-step LLM programs, adding tools to a model, or composing RAG systems in code.
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 and build LLM agents: ReAct loops, tool schemas, planning, memory, guardrails, evals, and human-in-the-loop. Use when building autonomous multi-step AI systems.
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。