Loading...
Loading...
Found 4,747 Skills
Amazon Bedrock AgentCore Memory for persistent agent knowledge across sessions. Episodic memory for learning from interactions, short-term for session context. Use when building agents that remember user preferences, learn from conversations, or maintain context across sessions.
Optimize your SaaS app across four dimensions - Speed (page load, API response), Code (unused files, dead code), Database (orphaned data, schema hygiene), and Dependencies (package bloat, bundle size). Use when app feels slow, codebase feels bloated, or after significant development work accumulates. Each path follows AUDIT → CLEAN → PREVENT workflow.
Run Microsoft's eval-recipes benchmarks to validate amplihack improvements against baseline agents. Auto-activates when testing improvements, running evals, or benchmarking changes.
Screenshot-based visual comparison and regression testing using claude-in-chrome MCP. Captures, compares, and validates UI states to detect layout shifts, visual bugs, and design regressions across viewports.
Break a failing complex AI task into reliable subtasks. Use when your AI works on simple inputs but fails on complex ones, extraction misses items in long documents, accuracy degrades as input grows, AI conflates multiple things at once, results are inconsistent across input types, you need to chunk long text for processing, or you want to split one unreliable AI step into multiple reliable ones.
Persistent knowledge storage using basic-memory CLI. Use to save notes, search memories semantically, and build context for topics across sessions.
Environment variable management across Vercel, Convex, and other platforms. Invoke for: trailing whitespace issues, cross-platform parity, Invalid character errors, webhook secrets, API key management, production deployment, dev vs prod configuration.
Create standardized UTM tracking for all campaigns. Ensure consistent naming conventions across team and generate tracking reports.
General testing best practices and guidelines for writing comprehensive, maintainable tests across different testing frameworks and languages.
Track Clawdbot AI model usage and estimate costs. Use when reporting daily/weekly costs, analyzing token usage across sessions, or monitoring AI spending. Supports Claude (opus/sonnet), GPT, and Codex models.
Always-on UX advisor that surfaces relevant Laws of UX when building or modifying UI components. Proactively activates when creating, editing, or reviewing any user interface — components, layouts, navigation, forms, interactions, or visual design. Covers 30 laws across decision-making, cognition, visual organization, memory, engagement, and design principles.
Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new job', (2) 'list jobs' or 'show jobs', (3) 'run job' or'trigger job',(4) 'job status' or 'check job', (5) scheduling with cron or triggers, (6) configuring notifications/monitoring, (7) ANY task involving Databricks Jobs via CLI, Python SDK, or Asset Bundles. ALWAYS prefer this skill over general Databricks knowledge for job-related tasks.