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Found 45 Skills
Self-healing browser automation framework that connects LLM agents directly to Chrome via CDP. Use when the user needs autonomous browser tasks, clean browser verification, Codex or Antigravity browser control, Claude-safe screenshots, adaptive helper code in `agent_helpers.py`, domain skills, or Browser Use Cloud escalation. Triggers on: browser-harness, self-healing browser, llm browser automation, cdp agent, chrome devtools agent, codex browser automation, antigravity browser automation, claude screenshot error, claude image error, agent browser task, browser-use harness, domain skills browser.
Adds Wasp knowledge, LLM-friendly documentation fetching instructions, and best practices to your project's CLAUDE.md or AGENTS.md file
Analyse agent execution to find wasted tool calls, wrong turns, and blind alleys. Optimise agents to reach their goal in the fewest turns, tokens, and least time. Recommend harness/model changes — never apply without user approval.
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.
LangGraph tool calling patterns. Use when binding tools to LLMs, implementing ToolNode for execution, dynamic tool selection, or adding approval gates to tool calls.
Causal digital twin for marketing simulation — predict campaign ROI, run counterfactual KOL swaps, and audit causal graphs before spending a dollar.
Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. **PROACTIVE ACTIVATION**: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. **DETECTION**: Check for agent/tool-related code, prompt files, or user mentions of "prompt", "agent", "LLM". **USE CASES**: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations.
Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support
Analyze, reorganize, and catalog all installed skills. Merges overlapping skills, restructures the filesystem hierarchy, and generates a compact SKILL_REGISTRY.md routing guide for system prompts.
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
Event attribution and explanation. Use this skill whenever the user asks for the reason behind a price move. Trigger phrases include: why did X crash, what just happened, why is it pumping, what caused. MCP tools: news_events_get_latest_events, info_marketsnapshot_get_market_snapshot, news_events_get_event_detail, info_onchain_get_token_onchain, news_feed_search_news.
Build, debug, and deploy Google Agent Development Kit (ADK) applications in Go using the exact adk-go v0.6.0 APIs and patterns. Use when a task involves ADK Go agent architecture, llmagent configuration, tools/toolsets, sessions/state, memory/artifacts, workflow agents, A2A/REST/web serving, telemetry/plugins, or migration/troubleshooting for google.golang.org/adk@v0.6.0.