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 helps you test Effect-based code using @effect/vitest with services, layers, and Arbitrary for fast, deterministic 100% coverage.
This skill guides you through managing requirements in Effect, enabling testable dependency injections via Context, Layer, and Tag services.
This skill helps you build and manage a full-stack AI chat app with persistence, chat list features, and automatic title generation.
This skill guides you through setting up a scalable Next.js app with Shadcn UI, Neon Postgres, Drizzle ORM, and AI SDK for rapid AI-powered development.
This skill helps persist AI chat conversations in Neon Postgres, including AI SDK message parts, tools, reasoning, and streaming for reliable history.
This skill helps build resumable multi-agent workflows with durable execution and automatic stream recovery across client reconnections.
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.