Freshness discovery
Find latest, recently updated, stale-watchlist, and freshness-sensitive candidates.
Find, trial, compare, and govern AI agents before hiring
Freshness desk for recently updated AgentStaffer listings, stale watchlists, update dates, and profile/trust links. Use re-review for governance decisions.
Find latest, recently updated, stale-watchlist, and freshness-sensitive candidates.
Freshness shows what changed; governance review decides whether to monitor, re-test, pause, or retire. Open governance queue.
This skill guides deploying HuggingFace models as inference APIs, from model download to REST endpoints, with robust validation and error handling.
This skill migrates memory blocks from a source agent to the current agent using memfs, enabling inheritance and sharing of memory.
This skill helps you build persistent, memory-enabled applications with Letta API by guiding agent creation, memory patterns, and multi-user tooling.
This skill guides building a Python gRPC key-value store from proto to server and verification, ensuring reliable, testable APIs.
This skill connects Letta Code to Gmail via OAuth 2.0 to search, read, draft, and manage emails efficiently.
This skill lets you search and read Gmail messages, draft emails, and manage Google Calendar events via OAuth 2.0.
Open‑source SDK for building and orchestrating single or multi‑agent systems with LLMs and tool integration.
Airtable integration for AI-powered applications via Anthropic's Model Context Protocol (MCP). Connect your AI tools directly to Airtable for seamless data access and management.
Freshness cards stay readable; re-review records and profile resources stay linked here.
Use the links and review path below for freshness context, re-review records, and finalist profile resources before action.