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概要と使いどころ
Implements secure authentication patterns including login/registration, session management, JWT tokens, password hashing, cookie settings, and CSRF protection. Provides auth routes, middleware, security configurations, and threat model documentation. Use when building "authentication", "login system", "JWT auth", or "session management".
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 a project directory or a website URL into a short, shareable launch video with music, motion, and share copy. One file, no bundled assets — built entirely by the model with the tools already on the machine. Use when someone says "/brag-slim", "let's /brag about this", "brag about <url>", "make a launch video", or wants to show off what they built. If the /brag skill is also installed, let /brag handle those phrases; it hands off here on Opus 5.5.
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 when AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.
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。
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation ...
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。
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass...
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。
LLM bugs are only worth reporting when they cross a trust boundary you can prove — an OOB callback, a verbatim-reproducible secret, a cross-tenant record, or code execution. A model 'saying something bad once' is confabulation, not a vulnerability. Read the False-Positive Gate before claiming anything.
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 security offensive checklist: prompt injection, jailbreaking, model extraction, training data poisoning, adversarial inputs, LLM-assisted attack automation, and AI system reconnaissance. Use when assessing AI/ML systems, red-teaming LLMs, or researching AI attack vectors.
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。
Fix common cron job failures in Clawdbot/Moltbot - message delivery issues, tool timeouts, timezone bugs, and model fallback problems.
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。
Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I
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。
Local speech-to-text using faster-whisper. 4-6x faster than OpenAI Whisper with identical accuracy; GPU acceleration enables ~20x realtime transcription. Supports standard and distilled models with word-level timestamps.
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。
Production-grade AI trading agent for cryptocurrency markets with advanced mathematical modeling, multi-layer validation, probabilistic analysis, and zero-hallucination tolerance. Implements Bayesian inference, Monte Carlo simulations, advanced risk metrics (VaR, CVaR, Sharpe), chart pattern recognition, and comprehensive cross-verification for real-world trading application.
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 when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
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。
Run the Model Context Protocol (MCP) Atlassian server in Docker, enabling integration with Jira, Confluence, and other Atlassian products. Use when you need to query Jira issues, search Confluence, or interact with Atlassian services programmatically. Requires Docker and valid Jira API credentials.
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 when designing REST or GraphQL APIs, creating OpenAPI specifications, or planning API architecture. Invoke for resource modeling, versioning strategies, pagination patterns, error handling standards.
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。
Check Antigravity account quotas for Claude and Gemini models. Shows remaining quota and reset times with ban detection.
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 custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.
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。
Complete community building, engagement, and monetization system. From zero to thriving community — launch strategy, member engagement loops, content programming, moderation frameworks, growth tactics, monetization models, and health metrics. Works for Discord, Slack, Telegram, Circle, forums, or any platform.
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。
Set up Rei Qwen3 Coder as a model provider. Use when configuring coder.reilabs.org, adding Rei to Clawdbot, or troubleshooting 403 errors from Rei endpoints.
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。
Unified LLM Gateway - One API for 70+ AI models. Route to GPT, Claude, Gemini, Qwen, Deepseek, Grok and more with a single API key.
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。
End-to-end MegaETH development playbook (Feb 2026). Covers wallet operations, token swaps (Kyber Network), eth_sendRawTransactionSync (EIP-7966) for instant receipts, JSON-RPC batching, real-time mini-block subscriptions, storage-aware contract patterns (Solady RedBlackTreeLib), MegaEVM gas model, WebSocket keepalive, bridging from Ethereum, and debugging with mega-evme. Use when building on MegaETH, managing wallets, sending transactions, or deploying contracts.
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 US stock analysis with financial data, news, social sentiment, and multi-model AI. Comprehensive reports at $0.02-0.10 per analysis.
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。
Interact with the BNB Chain Model Context Protocol (MCP) server. Use to query DeFi data, get token prices, search documentation, fetch git diffs, and retrieve smart contract source code on BNB Chain.
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 for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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。
Analyze any codebase's source code in depth and produce structured analysis documents saved as markdown files. Use this skill whenever the user asks to understand how a codebase works — architecture, module design, call flows, data models, design patterns, performance characteristics, or any implementation detail. Trigger on phrases like "analyze the source", "explain this code", "how does X work", "where is Y implemented", "trace the flow of", "what happens when", "read through the code", "code walkthrough", "源码分析", "代码解读", "实现原理", "架构分析", "调用链路", "模块分析", or any code-exploration request. Works with any programming language: TypeScript/JavaScript, Java, Python, Go, Rust, C/C++, and more. Even if the user's question seems simple (e.g., "这个文件是干什么的"), use this skill — a thorough, source-backed analysis document is always more valuable than a surface-level guess.
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。