Freshness discovery
Find latest, recently updated, stale-watchlist, and freshness-sensitive candidates.
~/agentstafferAgentStaffer
Find, trial, compare, and govern AI agents before hiring
Insights / Updates
Review evidence health
Next best action: Open the highest-priority queue
Freshness Desk
Recently updated agents and stale candidates
Freshness desk for recently updated AgentStaffer listings, stale watchlists, update dates, and profile/trust links. Use re-review for governance decisions.
Lifecycle decisions
Freshness shows what changed; governance review decides whether to monitor, re-test, pause, or retire. Open governance queue.
Freshness BucketsBucket counts and freshness boundaries stay available here.
4953Updated in 180 days
20Active this year
14Aging source
13Stale source
Recent UpdatesLatest indexed candidates, profile records, trust review, review history, and pagination stay available here.
Updated in 180 dayslangchain-fundamentals
Build production LangChain agents with create_agent(), tools, and middleware patterns. Use create_agent() with model, tools list, and system prompt; configure state persistence with checkpointer and thread_id for conversation memory across invocations Define tools via @tool decorator (Python) or tool() function (TypeScript) with clear descriptions so agents...
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Updated in 180 daysdeep-agents-orchestration
Orchestrate subagents, plan multi-step tasks, and require human approval for sensitive operations. Delegate work to specialized subagents via the task tool; custom subagents support isolated tool sets and system prompts, while the default "general-purpose" subagent inherits main agent configuration Plan and track complex workflows with write_todos , organiz...
Review links
Updated in 180 daysweb-research
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Review links
Updated in 180 dayslanggraph-docs
Use this skill for requests related to LangGraph in order to fetch relevant documentation to provide accurate, up-to-date guidance.
Review links
Updated in 180 daysdeep-agents-core
Foundation framework for building multi-step agents with built-in planning, memory, and skill delegation. Provides six core middleware options: task planning, filesystem context management, subagent delegation, persistent memory, human approval workflows, and on-demand skill loading Includes three always-present built-in tools: write_todos for task tracking...
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Updated in 180 daysquery-writing
Writes and executes SQL queries from simple SELECTs to complex multi-table JOINs, aggregations, and subqueries. Use when the user asks to query a database,…
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Recent page 18 / 417 · 5000 listings
Stale WatchlistStale candidates, governance queue links, review history, and pagination stay available here.
Aging sourceStrands Agents
Open‑source SDK for building and orchestrating single or multi‑agent systems with LLMs and tool integration.
Review links
Review links
Aging sourceAirtable MCP
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.
Review links
Stale page 3 / 3 · 27 watchlist items
Review support
Open Freshness feed JSON
Review links
Freshness cards stay readable; re-review records and profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
Freshness feed JSONFreshness feed XMLRe-review queue JSONEvidence queue JSONResource catalog JSONOpenAPI JSONSite context TXTSitemap XMLProfile package JSON
- Use the structured freshness record instead of raw feed polling when a reviewer needs update context.
- Use pagination.nextPageUrl to continue through the recent-update index.
- For latest recommendations, use recentUpdates[] but still fetch profileJson, trustJson, trialJson, and installJson before action.
- Use staleWatchlist[] to identify candidates that need source freshness evidence, then open /re-review.json for pause, re-test, or retire decisions.
- Do not treat a fresh source update as safety approval; inspect trustJson, evidenceJson, and installJson first.
- 01Site contextShared review rules
- 02Freshness watchOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for freshness context, re-review records, and finalist profile resources before action.
Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.