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.
4951Updated in 180 days
22Active this year
14Aging source
13Stale source
Recent UpdatesLatest indexed candidates, profile records, trust review, review history, and pagination stay available here.
Updated in 180 daysmongoose skill by toilahuongg/shopify-agents-kit
This skill guides secure, TypeScript-first Mongoose usage with performance best practices for MongoDB, enabling faster, type-safe data access in modern apps.
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This skill helps you use the Upstash Redis SDK for serverless caching, sessions, rate limiting, and data structures with automatic serialization.
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Updated in 180 daysuniapp skill by uni-helper/skills
This skill helps you develop cross-platform uni-app apps by applying official guidance across platforms, components, and lifecycle with best-practice patterns.
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Updated in 180 daysliterature-review skill by u9401066/med-paper-assistant
系統性文獻搜尋、篩選、下載、整理。觸發：文獻回顧、找論文、搜尋文獻、systematic review、literature search、PubMed、找文章、搜paper、review、reference、citation、引用、參考文獻、背景調查、background。
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Updated in 180 daystester skill by truongnat/agentic-sdlc
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Recent page 56 / 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.
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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.
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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.