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Topic: openai

1,087 skills in this topic.

audiocraft-audio-generation PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.
NousResearch/hermes-agent 56,643
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.
NousResearch/hermes-agent 56,643
segment-anything-model Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
NousResearch/hermes-agent 56,643
stable-diffusion-image-generation State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.
NousResearch/hermes-agent 56,643
whisper OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
NousResearch/hermes-agent 56,643
dspy Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
NousResearch/hermes-agent 56,643
axolotl Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
NousResearch/hermes-agent 56,643
grpo-rl-training Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
NousResearch/hermes-agent 56,643
peft-fine-tuning Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
NousResearch/hermes-agent 56,643
code-change-verification Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents Python repository.
openai/openai-agents-python 20,562
docs-sync Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync docs with code, or propose doc updates/structure changes. Only update English docs under docs/** and never touch translated docs under docs/ja, docs/ko, or docs/zh. Provide a report and ask for approval before editing docs.
openai/openai-agents-python 20,562
examples-auto-run Run python examples in auto mode with logging, rerun helpers, and background control.
openai/openai-agents-python 20,562
final-release-review Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-python.
openai/openai-agents-python 20,562
implementation-strategy Decide how to implement runtime and API changes in openai-agents-python before editing code. Use when a task changes exported APIs, runtime behavior, serialized state, tests, or docs and you need to choose the compatibility boundary, whether shims or migrations are warranted, and when unreleased interfaces can be rewritten directly.
openai/openai-agents-python 20,562
openai-knowledge Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.
openai/openai-agents-python 20,562
pr-draft-summary Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-python. Use in the final handoff after moderate-or-larger changes to runtime code, tests, examples, build/test configuration, or docs with behavior impact; skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.
openai/openai-agents-python 20,562
runtime-behavior-probe Plan and execute runtime-behavior investigations with temporary probe scripts, validation matrices, state controls, and findings-first reports. Use only when the user explicitly invokes this skill to verify actual runtime behavior beyond normal code-level checks, especially to uncover edge cases, undocumented behavior, or common failure modes in local or live integrations. A baseline smoke check is fine as an entry point, but do not stop at happy-path confirmation.
openai/openai-agents-python 20,562
test-coverage-improver Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
openai/openai-agents-python 20,562
csv-workbench Analyze CSV files in /mnt/data and return concise numeric summaries.
openai/openai-agents-python 20,562
repomix Pack and analyze codebases into AI-friendly single files using Repomix. Use when the user wants to explore repositories, analyze code structure, find patterns, check token counts, or prepare codebase context for AI analysis. Supports both local directories and remote GitHub repositories.
yamadashy/repomix 23,364
agent-memory Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.
yamadashy/repomix 23,364
contextual-commit Write contextual commits that capture intent, decisions, and constraints alongside code changes. Use when committing code, finishing a task, or when the user asks to commit. Extends Conventional Commits with structured action lines in the commit body that preserve WHY code was written, not just WHAT changed.
yamadashy/repomix 23,364
repomix-explorer Use this skill when the user wants to analyze or explore a codebase (remote repository or local repository) using Repomix. Triggers on: 'analyze this repo', 'explore codebase', 'what's the structure', 'find patterns in repo', 'how many files/tokens'. Runs repomix CLI to pack repositories, then analyzes the output.
yamadashy/repomix 23,364
browser-extension-developer Use this skill when developing or maintaining browser extension code in the `browser/` directory, including Chrome/Firefox/Edge compatibility, content scripts, background scripts, or i18n updates.
yamadashy/repomix 23,364