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Found 3,748 Skills
Analyze community opinions from forums and comment sections. Scrapes comments from Bilibili, Reddit, or GitHub Issues, clusters them by semantic similarity, and extracts the core arguments, debates, and viewpoints. Produces a structured report showing what the community actually thinks — not just a summary of comments, but the underlying positions people hold and where the real disagreements are. Use this skill when the user wants to understand public opinion on a topic, find the main points of contention in a discussion, or do competitive/event research from community sources. Triggers include requests to "analyze comments", "what are people saying about X", "summarize the debate", "find the key arguments", "what's the community consensus", or any task involving opinion extraction from forum or comment data.
Automates the Karpathy LLM Wiki workflow: turns web, GitHub, and YouTube URLs into well-structured, citable, wikilinked pages with automatic linting and sourcing — invoke with /pin-llm-wiki
Summarizes WeChat group chat highlights into a structured digest using the local wx-cli binary (https://github.com/jackwener/wx-cli). Generates a normal digest by default; a roast (毒舌) version is opt-in. Maintains per-group history (history.json + history-digests.jsonl) and per-user profiles across runs, with privacy guardrails baked in. Use when the user asks to "总结群聊", "群聊精华", "群聊摘要", "summarize group chat", "group chat digest", mentions a WeChat group name with a time range, says "帮我看看 XX 群最近聊了什么", "XX 群有什么值得看的", or asks to "回溯画像" / "初始化画像" / "backfill profiles". Adds the roast version when the user says "毒舌版", "roast 版", "再来个毒舌的", or similar.
Read and parse DLIS (Digital Log Interchange Standard) and LIS (Log Information Standard) well log files. Use when Claude needs to: (1) Read/parse DLIS or LIS files, (2) Extract well log curves as numpy arrays, (3) Access file metadata and origin information, (4) Handle multi-frame or multi-file DLIS, (5) Convert DLIS to LAS or DataFrame, (6) Work with RP66 format well logs, (7) Process array or image log data.
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (Node.js, Python, Go, Java, .NET, Ruby SDKs). Also walks through choosing and configuring machine identity auth methods (Universal Auth, AWS Auth, Kubernetes Auth, OIDC, etc.). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'.
Guide for configuring Infisical Secret Syncs to push secrets from Infisical to third-party services. Covers 38+ sync destinations including AWS Secrets Manager, GCP Secret Manager, Azure Key Vault, GitHub, Vercel, HashiCorp Vault, Cloudflare, and more. Use this skill when someone asks about: syncing secrets to AWS/GCP/Azure, pushing secrets to GitHub Actions, Vercel environment variables, secret sync setup, App Connections, mapping behavior, key schemas, or 'how do I get my Infisical secrets into [service]'.
Run a safe, reviewable Aider CLI coding loop for local repositories: model setup, edit scope control, test-first prompting, commit hygiene, and fallback when agent edits drift. Use when the user wants pair-programming with Aider, not generic Git workflow or hosted PR operations.
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing academic-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
Set up, configure, and troubleshoot Salesforce Code Analyzer for any project. Handles installation, prerequisite checks, diagnosing broken setups, creating and editing code-analyzer.yml overrides, engine-specific settings, ignore patterns, severity overrides, and CI/CD pipeline setup. TRIGGER when: user says 'set up code analyzer', 'configure code analyzer', 'install code analyzer', 'code analyzer not working', 'fix my setup', 'scan is failing', 'check my setup', 'is code analyzer installed', 'enable/disable engine', 'exclude files', 'change severity', 'set up GitHub Actions', 'set up CI/CD', 'add code analyzer to pipeline', 'make pipeline fail', 'update my workflow', 'quality gate', 'fail on violations', 'scan changed files only', 'add SARIF', 'code-analyzer.yml', 'ESLint config', 'increase SFGE memory', or reports errors running Code Analyzer. DO NOT TRIGGER when: user wants to run a scan (use running-code-analyzer), fix violations, explain rules, create custom rules, or suppress violations.
Complete PowerShell expertise system across ALL platforms (Windows/Linux/macOS). PROACTIVELY activate for: (1) ANY PowerShell task (scripts/modules/cmdlets), (2) CI/CD automation (GitHub Actions/Azure DevOps/Bitbucket), (3) Cross-platform scripting, (4) Module discovery and management (PSGallery), (5) Azure/AWS/Microsoft 365 automation, (6) Script debugging and optimization, (7) Best practices and security. Provides: PowerShell 7+ features, popular module expertise (Az, Microsoft.Graph, PnP, AWS Tools), PSGallery integration, platform-specific guidance, CI/CD pipeline patterns, cmdlet syntax mastery, and production-ready scripting patterns. Ensures professional-grade, cross-platform PowerShell automation following industry standards.
AWS Key Management Service (KMS) patterns using AWS SDK for Java 2.x. Use when creating/managing encryption keys, encrypting/decrypting data, generating data keys, digital signing, key rotation, or integrating encryption into Spring Boot applications.
Implement OAuth 2.0 social login with Google, GitHub, and other providers. Handles token exchange, user creation, and account linking.