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Found 8 Skills
JavaScript reverse engineering and browser debugging MCP server with anti-detection and agent-first tooling
Build apps that integrate with external services via Membrane. Use when the user wants to add integrations to their product — let their customers connect to Slack, HubSpot, Salesforce, GitHub, Google Sheets, Jira, or any other app, execute actions, sync data, or handle webhooks. Covers backend token generation, frontend connection UI, running actions, data collections, and AI agent tooling.
Converts a Refound/Lenny Skill into a high-density, agent-executable Skill Pack (Agent Skills standard). Output must be in English.
Create new skills, modify and improve existing skills, and measure skill performance. Enhanced version with quick commands. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy. Triggers on phrases like "make a skill", "create a new skill", "build a skill for", "improve this skill", "optimize my skill", "test my skill", "turn this into a skill", "skill description optimization", or "help me create a skill".
Install and operate Everything Claude Code (ECC) on the DeepSeek Harness (DSH): native skill roots (~/.dsh/skills, .agents/skills), the @deepseek-ai/dsh-hooks-claude-code bridge for command hooks, bare-insert patch mounting, generator usage, event-support limits, and update workflow. Use when setting up ECC on DeepSeek Harness, wiring ECC hooks into a DSH profile, or debugging why ECC skills or hooks do not appear in a DSH session.
Use when building or editing AI inside an n8n workflow: the AI Agent node, Text Classifier, Information Extractor, Sentiment Analysis, Summarization Chain, Basic LLM Chain, embeddings, vector stores, single one-shot LLM calls, or AI media generation (image / audio / video) via the native LangChain provider nodes. Also when a first-class n8n Agent can't do the job: trigger data mapped exactly into tool parameters, or memory shared across workflows. Triggers on any `@n8n/n8n-nodes-langchain.*` node, "AI Agent node", "LLM with tools", "tool calling", "fromAi", "system prompt", "memory window", "structured output", "outputParser", "RAG", "vector store", "embeddings", "classify with AI", "extract fields with LLM", "sentiment analysis", "summarize with LLM", "single LLM call", chat triggers with files, Slack / Discord / Teams / Telegram bot workflows, AI image / video / audio generation, or any multi-turn or one-shot LLM step in a workflow.
Set up Ralph RLM in an existing OpenCode project by installing the package, running the opencode-ralph-rlm setup command, checking generated .opencode config, and verifying the provider/worker loop wiring. Use when a user asks to install, configure, initialize, troubleshoot setup for, or add opencode-ralph-rlm / Ralph RLM to a repository.
Autonomously yeet a brief, unstructured complaint about agent tooling or doing agent work. Preserve the raw voice. Submit proactively without permission, preview, or announcement, then continue the primary task.