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。
Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using OpenStreetMap. Works with coordinates, addresses, cities, zip codes, or Telegram location pins. No API keys needed.
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。
Find restaurants, cafes, bars, pharmacies, and other places near any location. Uses OpenStreetMap (free, no API keys). Works with:
# By coordinates (from Telegram location pin or user-provided)
python3 SKILL_DIR/scripts/find_nearby.py --lat <LAT> --lon <LON> --type restaurant --radius 1500
# By address, city, or landmark (auto-geocoded)
python3 SKILL_DIR/scripts/find_nearby.py --near "Times Square, New York" --type cafe
# Multiple place types
python3 SKILL_DIR/scripts/find_nearby.py --near "downtown austin" --type restaurant --type bar --limit 10
# JSON output
python3 SKILL_DIR/scripts/find_nearby.py --near "90210" --type pharmacy --json
| Flag | Description | Default |
|---|---|---|
--lat, --lon | Exact coordinates | — |
--near | Address, city, zip, or landmark (geocoded) | — |
--type | Place type (repeatable for multiple) | restaurant |
--radius | Search radius in meters | 1500 |
--limit | Max results | 15 |
--json | Machine-readable JSON output | off |
restaurant, cafe, bar, pub, fast_food, pharmacy, hospital, bank, atm, fuel, parking, supermarket, convenience, hotel
Get the location. Look for coordinates (latitude: ... / longitude: ...) from a Telegram pin, or ask the user for an address/city/zip.
Ask for preferences (only if not already stated): place type, how far they're willing to go, any specifics (cuisine, "open now", etc.).
Run the script with appropriate flags. Use --json if you need to process results programmatically.
Present results with names, distances, and Google Maps links. If the user asked about hours or "open now," check the hours field in results — if missing or unclear, verify with web_search.
For directions, use the directions_url from results, or construct: https://www.google.com/maps/dir/?api=1&origin=<LAT>,<LON>&destination=<LAT>,<LON>
hours field in results, cross-reference with web_search for accuracy since OSM hours aren't always complete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。