openai | Agent Skills

sentry-setup-ai-monitoring

Setup Sentry AI Agent Monitoring in any project. Use this when asked to add AI monitoring, track LLM calls, monitor AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI. Automatically detects installed AI SDKs and configures the appropriate Sentry integration.

sentryai-monitoringintegrationllm

getsentry

clip

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

openaivision-languageimage-classificationzero-shot

ovachiever

ai-usage

Check AI CLI usage/quota for Claude Code, OpenAI Codex, Google Gemini CLI, and Z.AI. Use when user asks about remaining quota, usage limits, rate limits, or wants to check how much capacity is left.

cliquota-managementrate-limitsopenai

cruzanstx

openai-prompt-engineer

Generate and improve prompts using best practices for OpenAI GPT-5 and other LLMs. Apply advanced techniques like chain-of-thought, few-shot prompting, and progressive disclosure.

chain-of-thoughtfew-shot-promptingprogressive-disclosureopenai

zircote

ai-llm-development

transformersdeep-learningai-modelsopenai

phrazzld

multi-llm

Route tasks to optimal LLM provider (Gemini, Codex, Copilot, Claude)

multi-backendopenaiclaudellm-routing

HTRamsey

codex

Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing

openaiclicode-analysiscode-refactoring

rocky2431

streaming

Use when building real-time chat interfaces, displaying incremental LLM responses, or streaming output from OpenAI, Anthropic, Google, or Ollama - async iteration with usage tracking works across all providers

openaiai-modelsasynchronous-programmingstreaming

juanre

providers

Use when switching between LLM providers, accessing provider-specific features (Anthropic caching, OpenAI logprobs), or using raw SDK clients - covers multi-provider patterns and direct SDK access for OpenAI, Anthropic, Google, and Ollama

openaianthropicllm-providersapi

juanre

chat

Use when starting a new project with llmring, building an application using LLMs, making basic chat completions, or sending messages to OpenAI, Anthropic, Google, or Ollama - covers lockfile creation (MANDATORY first step), semantic alias usage, unified interface for all providers with consistent message structure and response handling

llmopenaiapimulti-backend

juanre

sdd-pr

AI-powered PR creation after spec completion. Analyzes spec metadata, git diffs, commit history, and journal entries to generate comprehensive PR descriptions with user approval before creation.

gitpull-requeststask-automationopenai

tylerburleigh

oracle

Use the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.

code-reviewcliopenaiprompt-engineering

gmickel

litellm

When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.

pythonllm-integrationopenaianthropic