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Found 946 Skills
Manages identity and access control for Google Cloud resources using IAM policies and roles.
Interact with Google Cloud Storage to manage buckets, objects, and access controls for scalable data storage.
Turn any record into a shared workspace where agents and humans collaborate. Attach a simple workspace schema to any entity — contacts, companies, deals, projects, tickets — and let any participant contribute updates, tasks, notes, and issues. The record becomes the coordination. No orchestrator, no message bus — just read the workspace, do your work, record what you did. Intelligence accumulates. Use when multiple agents, humans, or systems need to work on the same entity together.
Manages financial risks through quantitative analysis, modeling, and mitigation strategies.
Implements networking for multiplayer games, handling protocols, latency, and synchronization.
Manages organizational guidelines, policies, and best practices as governance variables accessible to all AI agents via SmartContext. Use when working with company rules, brand voice, compliance policies, playbooks, or when any task needs organizational context before proceeding.
Stores and retrieves persistent memory about records — contacts, companies, employees, members, and more. Handles memorization (single and batch with per-property AI extraction), semantic recall, entity digests, and data export. Use when storing data, syncing records, querying memory, or assembling context for personalization.
Create a minimal working Vast.ai example. Use when starting a new Vast.ai integration, testing your setup, or learning basic Vast.ai API patterns. Trigger with phrases like "vastai hello world", "vastai example", "vastai quick start", "simple vastai code".
List available large language models and send chat completion requests programmatically. Use this skill when you need to call an LLM within a snippet, including model comparison, visual understanding, batch inference, and model performance testing.
Add Olakai monitoring to existing AI code — wrap your LLM client, configure custom KPIs, and validate the integration end-to-end