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Found 7,489 Skills
This skill should be used when the user asks to "create a plan for replit", "break down tasks", "create development phases", "checkpoint strategy", or needs to convert a project into iterative development phases that Replit Agent can execute step-by-step with checkpoints.
This skill should be used when the user asks to "create a replit prompt", "write a prompt for replit", "optimize for replit agent", "prepare instructions for replit", or mentions building something with Replit Agent. Transforms user requirements into optimized, structured prompts that Replit Agent understands and executes accurately with minimal iterations.
Use this agent when working with prompt injection detection integration tests, including running tests, debugging failures, or adding new test samples.
Structured clarification before decisions. Use when user is in PLANNING mode, explicitly asks to plan or discuss, or when agent faces choices requiring user input. Ensures agent asks questions instead of making autonomous decisions when multiple valid approaches exist or context is missing.
Detects ESLint configuration and available commands in a repository. Returns structured JSON output designed for consumption by the quality-gates-linter agent. Checks for ESLint config files, extracts lint commands from package.json, Makefile, and CLAUDE.md, and provides command sources for the agent to read directly.
Writes agent outputs to numbered thread stage files. Called by agents after domain work completes. Maps agent type to stages, updates frontmatter status, and records completion metadata. Stage 1 (1-input.md) is never written by this skill.
Expert in load balancing and dynamic task allocation for multi-agent systems. Specializes in optimal routing based on agent capability, availability, and cost (Token Economics).
Expert in making multi-agent systems resilient. Specializes in detecting loops, hallucinations, and failures, and implementing self-healing workflows. Use when designing error handling for agent systems, implementing retry strategies, or building resilient AI workflows.
Expert in observing, benchmarking, and optimizing AI agents. Specializes in token usage tracking, latency analysis, and quality evaluation metrics. Use when optimizing agent costs, measuring performance, or implementing evals. Triggers include "agent performance", "token usage", "latency optimization", "eval", "agent metrics", "cost optimization", "agent benchmarking".
Lead coordinator that orchestrates 5 news scraper agents in parallel to gather headlines from 15 top business news websites
Comprehensive research and synthesis agent specializing in multi-source information gathering, critical analysis, and integrated knowledge synthesis. Excels at complex research projects requiring systematic investigation across domains, evidence evaluation, and coherent narrative construction.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration