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概要と使いどころ
CTF challenge ana orkestratörü — kategori tespiti, modern saldırı patern tanıma, ilgili skill arama, cross-skill zincir koordinasyonu, hızlı referans erişim. Auto-solver ve hint-system routing.
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。
Framer Motion React animation library skill — declarative animations, gestures, layout transitions, scroll-triggered animations, variants, AnimatePresence, and performance optimization.
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。
Crypto kategori SKILL.md — RSA, ECC, AES, hash, encoding saldırıları için gerekli araçları kurma rehberi
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。
Pwn/Binary kategorisi SKILL.md — BOF, ROP, kernel exploit araçları kurma rehberi
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。
ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (the default polling pattern) or a single supervised `unique-cli elicit ask` call (only when your agent instructions say your environment supervises the wait) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.
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。
Git worktree を使った並列開発時に使用。配置・ポート割当・環境コピー・クリーンアップを標準化する。
Use when helping users configure LoRA training — select presets, understand parameters, and pick the right settings for their model type. Covers SD1.5, SDXL, SD3, and Flux1 with real-world presets.
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, edit, or debug parametric 3D CAD parts in CadQuery (Python) that export to STEP for SolidWorks. Use when the request involves CadQuery, .step/.stl export, or modelling a physical part — enclosure, bracket, PCB, motor mount, cam, gear. Also use when a STEP will not open in CAD, or geometry looks correct in STL but is invalid as a solid. Applies a verification discipline before export and documented OCC pitfalls.
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。
Short-drama and product-video development skill for planning drama projects through a bundled Busabase App-in-Skill UI, with each project linked to a specified HyperFrame project and each episode linked to a HyperFrame composition for final motion/video tuning. Use when the user asks to create, edit, organize, or review short-drama scripts, product explainer episodes, character consistency cards, series bibles, episode beat sheets, storyboard shots, HyperFrame project/composition links, production checklists, or a drama planning workbench.
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。
Finish an existing Japanese creator, challenge, comeback, vlog, or community-building vertical social rough cut as an evidence-grounded short-form story. Use for strong opening declarations, identity and struggle arcs, crisis-to-goal recovery, multi-source B-roll and evidence stills, emotional typography, semantic punch-ins, pinned SFX, dialogue-first audio, platform-added music delivery, and creator-short retention QA.
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。
Join and interact with CrabSpace - the MySpace-style social network for AI agents. Use when creating a profile, customizing appearance, managing friends, or posting on comment walls. Handles registration, tweet verification, profile updates, and social features.
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。
Delegate independent research, implementation, or verification in parallel when it can save time after dispatch and review overhead, or when explicitly requested. Keep decisions and final integration in the main agent.
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。
Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.
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。
Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.
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。
Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack campaigns require cross-organizational analysis, or when building campaign-level intelligence products. Activates for requests involving campaign analysis, incident clustering, cross-organizational IOC correlation, or MISP correlation engine.
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。
Responds to phishing incidents by analyzing reported emails, extracting indicators, assessing credential compromise, quarantining malicious messages across the organization, and remediating affected accounts. Covers email header analysis, URL/attachment sandboxing, and mailbox-wide purge operations. Activates for requests involving phishing response, email incident, credential phishing, spear phishing investigation, or phishing remediation.
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 Microsoft's Enhanced Security Admin Environment (ESAE) tiered administration model for Active Directory. Covers Tier 0/1/2 separation, privileged access workstations (PAWs), administrative f
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 a structured ransomware incident response playbook aligned with the CISA StopRansomware Guide and NIST Cybersecurity Framework. Covers preparation, detection, containment, eradication, recovery, and post-incident phases with actionable checklists. Activates for requests involving ransomware response planning, CISA compliance, incident response playbook creation, or ransomware preparedness assessment.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
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。
Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.
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 changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
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。
Plan a user interview topic in PostHog — pick who to target (cohort, emails, or PostHog distinct IDs), draft what to ask about, and prepare the voice-agent context plus a question list. Use when the user asks to "talk to users", "check how users feel about X", "interview some customers", "set up a user interview", "run a user-research call", "find users to ask about Y", or otherwise wants qualitative feedback through a conversation. Walks the user through targeting (cohorts-list, persons-list, or accepting emails / distinct IDs directly), captures the topic, and prompts for agent context and questions before calling user-interview-topics-create. Cohort targeting is resolved to explicit emails/distinct_ids at create time — topics snapshot their audience and do not re-evaluate cohort membership later. Do NOT trigger when the user is uploading a recorded interview audio file (that's the separate UserInterview/transcript flow) or only browsing existing topics with user-interview-topics-list.
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。