Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
日本語の概要は準備中です。原文の説明を表示しています。
Search and download GIFs from Tenor using curl. No dependencies beyond curl and jq. Useful for finding reaction GIFs, creating visual content, and sending GIFs in chat.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Search and download GIFs directly via the Tenor API using curl. No extra tools needed.
Set your Tenor API key in your environment (add to ~/.hermes/.env):
TENOR_API_KEY=your_key_here
Get a free API key at https://developers.google.com/tenor/guides/quickstart — the Google Cloud Console Tenor API key is free and has generous rate limits.
curl and jq (both standard on macOS/Linux)TENOR_API_KEY environment variable# Search and get GIF URLs
curl -s "https://tenor.googleapis.com/v2/search?q=thumbs+up&limit=5&key=${TENOR_API_KEY}" | jq -r '.results[].media_formats.gif.url'
# Get smaller/preview versions
curl -s "https://tenor.googleapis.com/v2/search?q=nice+work&limit=3&key=${TENOR_API_KEY}" | jq -r '.results[].media_formats.tinygif.url'
# Search and download the top result
URL=$(curl -s "https://tenor.googleapis.com/v2/search?q=celebration&limit=1&key=${TENOR_API_KEY}" | jq -r '.results[0].media_formats.gif.url')
curl -sL "$URL" -o celebration.gif
curl -s "https://tenor.googleapis.com/v2/search?q=cat&limit=3&key=${TENOR_API_KEY}" | jq '.results[] | {title: .title, url: .media_formats.gif.url, preview: .media_formats.tinygif.url, dimensions: .media_formats.gif.dims}'
| Parameter | Description |
|---|---|
q | Search query (URL-encode spaces as +) |
limit | Max results (1-50, default 20) |
key | API key (from $TENOR_API_KEY env var) |
media_filter | Filter formats: gif, tinygif, mp4, tinymp4, webm |
contentfilter | Safety: off, low, medium, high |
locale | Language: en_US, es, fr, etc. |
Each result has multiple formats under .media_formats:
| Format | Use case |
|---|---|
gif | Full quality GIF |
tinygif | Small preview GIF |
mp4 | Video version (smaller file size) |
tinymp4 | Small preview video |
webm | WebM video |
nanogif | Tiny thumbnail |
+, special chars as %XXtinygif URLs are lighter weightまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
日本語の概要は準備中です。原文の説明を表示しています。
Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
日本語の概要は準備中です。原文の説明を表示しています。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。