OpenAI Automation
Automate OpenAI API operations -- generate responses with multimodal and structured output support, create embeddings, generate images, and list models via the Composio MCP integration.
multi-model-meta-analysis
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model.
fal-workflow
Generate workflow JSON files for chaining AI models
CQRS Implementation
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
Investor materials
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
quant-analyst
Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk analysis.
Together Reasoning
Use reasoning and thinking models on Together AI including DeepSeek R1, DeepSeek V3.1, Kimi K2-Thinking, and Qwen3 with thinking mode. Models output chain-of-thought in <think>...</think> tags before answering. Adjustable reasoning effort (low/medium/high). Use when users need reasoning models, chain-of-thought, step-by-step thinking, math/code/logic problem solving, or adjustable reasoning depth.
RAG Engineer
Expert in building Retrieval-Augmented Generation (RAG) systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, or document retrieval.
Investor Materials
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
antigravity-proxy
Set up and use Antigravity Claude Proxy — a free proxy server that exposes Anthropic-compatible API backed by Google's Antigravity Cloud Code. Provides free access to Claude (Opus, Sonnet) and Gemini (Flash, Pro) models. Use when configuring OpenClaw agents with free Claude/Gemini models, setting up proxy for Claude Code CLI, checking proxy health/quota, adding Google accounts, or troubleshooting proxy issues. Triggers on antigravity, proxy, free claude, free gemini, cloud code, model quota, proxy setup, openclaw model config.
Hugging Face CLI
Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models, datasets, or Spaces; upload files to Hub repositories; create repositories; manage the local cache; or run compute jobs on Hugging Face infrastructure. Covers authentication (interactive and token-based), file transfers, repository creation and tagging, cache inspection and removal, listings and metadata for models/datasets/Spaces/endpoints, environment diagnostics, and running cloud compute jobs (including GPU flavors) remotely.
Java Developer
Expert Java development skill covering Spring Boot, Jakarta EE, and plain Java across versions Java 8 through Java 21+. Use when asked to write, generate, review, architect, or improve Java code. Handles: creating REST APIs, designing domain models, generating boilerplate (entities, repositories, services, controllers), code review for correctness/scalability/security, performance optimization, JVM tuning guidance, concurrency patterns, and applying architecture patterns (layered, hexagonal, DDD). Triggers on any Java programming request.