ruflo-ai-team
claudeTenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results
6 skills · 6 commands · 4 agents · 1 MCP server
Stop being the switchboard between your AI agents — direct a team. Long-running desks with persistent journals, a shared bench, structured signals, and a TA that reads the room.
Plugin workshop from marketplace the-workshop in jennyf19/the-workshop. Commands read from the repo's manifest — 6 days ago.
bench-readRead artifacts from the shared bench — the workspace where desks leave findings, verdicts, and work products for each other and the operator.
desk-journalWrite, append, or read desk journal entries. The journal is persistent memory — what survives session boundaries. A good entry has: what was done, current state, next step.
desk-openCreate and open a new desk in the workshop. Sets up the folder structure, initial journal, and desk identity so the next session that sits down finds the trail.
signal-writeEmit structured agent signals — hands-up, blocked, done, checkpoint, partnership. Signals are written as JSON to .signals/ for dashboard consumption and noted in the journal for persistence.
workshop-createCreate a new workshop or use an existing directory as one. Handles two paths: (A) use an existing local directory the operator points at, or (B) create a new private GitHub repo in the signed-in account. Never creates a repo inside another repo.
Workshop TARoom coordinator for a multi-agent workshop. Sees all desks, routes work, tracks state, manages journals, and emits coordination signals. Not a desk — the person who sees the whole room.
Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results
6 skills · 6 commands · 4 agents · 1 MCP server
Guide developers through adding maps, places search, geocoding, routing, and other geospatial features with Amazon Location Service, including authentication setup, SDK integration, and best practices.
1 skill · 1 MCP server
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
6 skills · 7 commands · 4 agents
Claude Code native multi-agent orchestration with intelligent model routing across agents and skills. Zero learning curve. Maximum power.
85 skills · 20 commands · 19 agents · 1 MCP server · hooks
Per-deal-and-packaging Commercial domain. v2.8.0 ships 8 skills: orchestrator + pricing-strategist (model picker + Van Westendorp WTP + packaging) + deal-desk (deal scorer + discount approval routing + redline) + partnerships-architect (5-tier classifier + joint GTM + revshare modeler) + channel-economics (cost-to-serve + ROI + mix optimizer) + commercial-policy (data-backed discount matrix + exception flow + linter) + rfp-responder (Shipley structured RFP/RFI/RFQ + win-theme + winrate predictor, context: fork) + commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Hard rules: pricing outputs model+range (never a single number), deal outputs route to named human approver (never auto-approve), forecast outputs surface conversion assumption, RFP never invents claims for GAP requirements. 21 stdlib Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic), finance (close+report).
8 skills · 9 commands · 1 agent
Agent coordination and meta-programming - multi-agent orchestration, workflow automation, and safe refactor governance. Works best with other voltagent plugins installed.
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