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Found 942 Skills
Advanced prototype pollution playbook — server-side RCE, client-side gadgets, filter bypasses, and detection techniques. Companion to ../prototype-pollution/ for basics. Use when you've confirmed pollution and need to escalate to code execution or find framework-specific gadgets.
Traffic analysis and PCAP forensics playbook. Use when analyzing network captures including Wireshark filters, protocol analysis (HTTP/DNS/FTP/SMTP/USB/WiFi), data extraction, covert channel detection, PCAP repair, TLS decryption, and tshark command-line analysis.
retention-corp/coupang_partners의 로컬 Coupang MCP 호환 레이어로 쿠팡 상품 검색, 로켓배송 필터, 가격대 검색, 상품 비교, 베스트 상품, 골드박스 특가를 조회한다.
Use curated Korean trending-slang candidates plus best-effort Namu Wiki lookups to write witty Korean text with up-to-date slang, with conservative safety and freshness guardrails.
Generative ideation engine. Takes a domain, trend, question, or constraint and produces 15-30 novel possibilities — things that might be true, businesses that could exist, futures that could unfold. Spawns a team of 6 specialist agents — Signal Scout, Analogist, Inverter, Combinator, Contrarian, Futurist — who each generate ideas from a distinct creative angle. The lead cross-pollinates across agents, finds unexpected combinations, and ranks the output by novelty × plausibility. Use when the user says "brainstorm", "what could exist", "what's possible", "generate ideas", "what might be true", "possibilities", or presents a domain and wants divergent exploration rather than evaluation of a specific idea.
kimlawtech/korean-jangbu-for (Apache-2.0) 업스트림을 중심으로 한국 스타트업·1인 법인·프리랜서·개인사업자 장부 자동화와 사업자 세무 자료 정리, 원본 데이터 가져오기, 계정과목 태깅, 세무사 전달 CSV, 경영 리포트 생성을 안내하는 thin wrapper 스킬.
Create comprehensive technical specs for SDK gaps, feature modules, or system centralization efforts. Use when writing specs, PRDs, gap analysis documents, or planning centralization of scattered functionality into a single module. Triggers on "create spec", "write spec", "gap spec", "centralize", "fill the gap".
Identify codebase deepening opportunities based on the domain language in CONTEXT.md and decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
Provides image recognition capabilities for non-multimodal models (such as pure text models like deepseek-v4-pro, GLM-5.1, mimo-v2.5-pro, etc.). This skill is automatically triggered when the main model cannot recognize images, when users send screenshots/design drafts/UI screenshots for analysis, or when users say 'Look at this image', 'Analyze this screenshot', 'What's wrong with this image'. It also applies to any scenario where users paste images but the current model does not support image input. Supports simultaneous recognition of multiple images, with primary-backup fallback achieved by configuring multiple image recognition models. It can also be manually triggered using the commands /skill:vision-support or /vision. Iron Rule: The models configured for this skill are only used for image content recognition and will never participate in main logical reasoning. Note: If the current model is itself a multimodal model (such as Claude Sonnet 4, GPT-4o, Gemini, etc. that can directly recognize images), do not use this skill; let the main model recognize directly.
Edit and improve articles by restructuring sections, enhancing clarity, and tightening prose. Use this when users want to edit, revise, or improve an article draft.
Review changes starting from a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (Does the code comply with the coding standards documented in this repository?) and Spec (Does the code meet the requirements from the source issue/PRD?). The two reviews run in parallel sub-agents and report side by side. This applies when users want to review a branch, PR, in-progress changes, or request a "review since X".
Implement a piece of work based on PRD or a collection of issues.