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Found 1,635 Skills
Deep multi-platform intelligence analysis combining LinkedIn (profile, posts, activity), Twitter/X (tweets, engagement), Reddit (discussions, community), web presence (articles, GitHub, blogs), and company intelligence. Use when analyzing people for networking, sales, partnerships, or recruitment. Accepts LinkedIn URL or name+context. Produces comprehensive cross-platform reports with conversation strategies and strategic value assessment for AnySite.
Generate product changelog entries, X/Twitter posts, and Slack announcements for Leather wallet releases. Use when creating release communications including changelog entries for app.leather.io/changelog, announcement tweets (single or threads), and community Slack posts. Inputs may include verbal feature descriptions, Linear projects, or GitHub PRs.
Use this skill when working on infrastructure, DevOps, CI/CD, Kubernetes, cloud deployment, observability, or cost optimization. Activates on mentions of Kubernetes, Docker, Terraform, Pulumi, OpenTofu, GitOps, Argo CD, Flux, CI/CD, GitHub Actions, observability, OpenTelemetry, Prometheus, Grafana, AWS, GCP, Azure, infrastructure as code, platform engineering, FinOps, or cloud costs.
Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.
Manages Git worktrees for isolated parallel development. Creates worktrees in .github/worktrees/ with symlinked .env files.
Deep EVM smart contract security audit system. Use when asked to audit a contract, find vulnerabilities, review code for security issues, or file security issues on a GitHub repo. Covers 500+ non-obvious checklist items across 19 domains via parallel sub-agents. Different from the security skill (which teaches defensive coding) — this is for systematically auditing contracts you didn't write.
Review code changes in Tenzir projects. Use when auditing diffs or pull requests for bugs, security issues, missing tests, documentation drift, readability problems, performance regressions, user experience issues, or when deciding how to respond to GitHub review comments. Also use this skill whenever the user says "review", "look at this PR", "check my changes", "audit this diff", "what do you think of this code", or asks for feedback on any code they've written or changed — even if they don't explicitly say "code review."
Write, scaffold, and debug Go CLI applications with `github.com/spf13/cobra`. Use this skill whenever the user mentions Cobra, `cobra.Command`, a Go command-line app, subcommands, persistent or local flags, required flags, argument validation, shell completions, generated docs, or wants to build or refactor a cobra-based CLI.
Use this skill whenever a user wants to run, install, configure, or understand open-ralph-wiggum (ralph). This skill can be used by any AI assistant or IDE agent (GitHub Copilot, Claude Code, Cursor, Windsurf, etc.). Triggers on: "ralph", "ralph wiggum", "agentic loop", "iterative AI loop", "autonomous coding loop", "how to install ralph", "how to use ralph with Claude Code / Codex / Copilot / OpenCode", "ralph --agent", "ralph --tasks", "ralph --status", "--max-iterations", "--rotation", "how do I run ralph in VS Code / Cursor / JetBrains / Neovim", or any question about looping an AI coding agent until a task is done. Even if the user doesn't say "ralph" explicitly — if they want to run an AI agent in a loop until a promise tag appears in its output, use this skill.
Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use this skill when writing a PRD for a feature.