9 tagged large language model, measured the same way as everything else here.
Browse within: artificial-intelligence 8large-language-models 8llms 8openai 8
Skill Claude CodeCodex
Build and wire an AtomicAgent[InSchema, OutSchema] — schemas, AgentConfig, SystemPromptGenerator, provider client, history, hooks, optional context providers. Use when the user asks to "create an agent", "add another agent", "build an AtomicAgent", "wire up an agent", "make a planner/router/extractor agent", or runs…
Skill Claude CodeCodex
Build a BaseTool[InSchema, OutSchema] subclass — input/output schemas, BaseToolConfig, run() (and optional runasync()), env-driven secrets, typed failure outputs. Use when the user asks to "add a tool", "create a tool", "wrap an API as a tool", "build a BaseTool", "make a calculator/search/weather tool", or runs…
Skill Claude CodeCodex
Guide for the Atomic Agents Python framework — schemas, agents, tools, context providers, prompts, orchestration, and provider configuration. Use when code imports from atomicagents, defines an AtomicAgent, BaseTool, or BaseIOSchema, or the user asks about multi-agent orchestration or LLM-provider wiring in an…
Skill Claude CodeCodex
Troubleshooter for agentic-RL training, evaluation, and experiment design on LLM agents (single or multi-agent, multi-turn, tool-augmented). Routes a user's symptom to fixes anchored in the corpus. TRIGGER when: user is training, evaluating, or designing experiments for an RL-trained LLM agent; symptoms like reward…