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.
4938Updated in 180 days
35Active this year
14Aging source
13Stale source
Recent UpdatesLatest indexed candidates, profile records, trust review, review history, and pagination stay available here.
Updated in 180 daysblocklet-dev-setup skill by arcblock/agent-skills
Configure development environment for blocklet-type repositories. Supports parsing GitHub Issue URLs, Blocklet URLs, or problem descriptions to automatically locate repositories, check permissions, clone code, install dependencies, and start development server. Use `/blocklet-dev-setup` or say "help me fix the xxx blocklet issue", "I want to develop xxx blo...
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Updated in 180 daysaudit-support skill by anthropics/knowledge-work-plugins
This skill helps you design SOX 404 testing, sample selection, and documentation workflows to strengthen ICFR compliance.
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Updated in 180 daysdewey-docs skill by arach/dewey
This skill helps you generate agent-ready project documentation using Dewey, creating AGENTS.md, llms.txt, and install.md for AI agents.
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Updated in 180 daysapify-actor-development skill by apify/agent-skills
This skill guides you through developing, debugging, and deploying Apify Actors with best practices for reliable, scalable serverless automation.
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Updated in 180 daysapollo-mcp-server skill by apollographql/skills
This skill guides you through configuring Apollo MCP Server and using introspection tools to connect AI agents with GraphQL APIs.
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Updated in 180 daysapollo-connectors skill by apollographql/skills
This skill guides you to integrate REST APIs into a GraphQL supergraph using Apollo Connectors with @source and @connect.
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Recent page 310 / 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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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.