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Found 3,416 Skills
Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.
Comprehensive knowledge of amplihack framework architecture, patterns, and usage
Unvarnished technical criticism combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's BS-detection. Use when code/tests need harsh reality checks, certification schemes smell fishy, or technical decisions lack rigor. No sugar-coating, just surgical truth about what's broken and why.
Rent cars, manage Gold Plus Rewards, and access Hertz premium services
Multi-agent coordination patterns for OpenCode swarm workflows. Use when work benefits from parallelization or coordination. Covers: decomposition, worker spawning, file reservations, progress tracking, and review loops.
Transforms vague or simple user prompts into high-quality, structured, and high-performance AI instructions using systematic optimization techniques like XML tagging, few-shot examples, and Chain-of-Thought. Use this skill when you need to improve the reliability, accuracy, or formatting of an AI's output.
Discover patterns, rules, and interfaces through iterative analysis cycles. Use when analyzing business rules, technical patterns, security, performance, integration points, or domain-specific areas. Includes cycle pattern for discovery to documentation to review workflow.
Provides project management, task tracking, team coordination, and project delivery capabilities. Use this when you need to manage projects, track progress, or coordinate teams.
This skill should be used when the user asks to refactor specific files or directories, simplify recently changed code, clean up dead code in a limited scope, or invokes `/refactor` with paths or semantic queries.
Browser automation command reference and usage patterns for web testing, form filling, screenshots, and data extraction.
Context compression and summarization methodology. Techniques for reducing token usage while preserving decision-critical information.
Based on the Recursive Language Models (RLM) research by Zhang, Kraska, and Khattab (2025), this skill provides strategies for handling tasks that exceed comfortable context limits through programmatic decomposition and recursive self-invocation. Triggers on phrases like "analyze all files", "process this large document", "aggregate information from", "search across the codebase", or tasks involving 10+ files or 50k+ tokens.