openbb-terminal
claudeOpen-source investment research terminal integration - equity analysis, crypto tracking, macro indicators, portfolio optimization, and AI-powered financial insights using OpenBB Platform
6 commands · 4 agents
Calculate 3-year ROI of moving forecasting to Nixtla TimeGPT, generate a real PDF report, compare scenarios with sensitivity analysis, and post the result to Salesforce as an Opportunity (live or dry-run).
Not in a marketplace yet, so it loads for one session with --plugin-dir.
Plugin nixtla-roi-calculator in jeremylongshore/plugins-nixtla. Commands read from the repo's manifest — 29 days ago.
This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.
/nixtla-roi-calculator:nixtla-roiCalculate TimeGPT ROI for enterprise customers
nixtla-roi-calculatorruns: python scripts/roi_calculator_mcp.py
Problems found in this repo's manifests
Open-source investment research terminal integration - equity analysis, crypto tracking, macro indicators, portfolio optimization, and AI-powered financial insights using OpenBB Platform
6 commands · 4 agents
Comprehensive operations manager for FairDB managed PostgreSQL service - SOPs, incident response, monitoring, and automation
6 commands · 3 agents
Comprehensive operations manager for FairDB managed PostgreSQL service - SOPs, incident response, monitoring, and automation
6 commands · 3 agents
Complete operations kit for FairDB PostgreSQL as a Service - VPS setup, PostgreSQL management, customer provisioning, monitoring, and backup automation
1 skill · 4 commands · 1 agent
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)
1 skill · 3 commands · 1 agent
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)
1 skill · 3 commands · 1 agent
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
Evaluate feature investments using revenue impact, cost structure, ROI, and strategy.
1 skill
Trading card market prices and grading ROI through one remote MCP server. Raw and graded prices for 1.5M+ Pokémon, Magic, Yu-Gi-Oh!, One Piece, Lorcana and sports cards, PSA 9 and PSA 10 premiums, net profit after grading fees, price history, 30-day movers and priced set checklists. Read-only, no account, no API key.
1 skill · 1 MCP server
Calculate and present ROI for AI automation projects
1 command
Executable business calculators & models — each ships a stdlib script: Unit Economics (LTV/CAC), SaaS Metrics (NRR/quick ratio), Runway (default alive/dead), Pricing, ROI/NPV — plus computed models that emit real .xlsx with live formulas: cohort curve fitting (LTV), Monte Carlo runway (P10/P50/P90), and Van Westendorp pricing. Verifiable math, not vibes.
30 skills
Use this agent when planning 6-day development cycles, prioritizing features, managing product roadmaps, or making trade-off decisions. This agent specializes in maximizing value delivery within tight timelines. Examples:\n\n<example>\nContext: Planning the next sprint\nuser: "We have 50 feature requests but only 6 days"\nassistant: "I'll help prioritize for maximum impact. Let me use the sprint-prioritizer agent to create a focused sprint plan that delivers the most value."\n<commentary>\nSprint planning requires balancing user needs, technical constraints, and business goals.\n</commentary>\n</example>\n\n<example>\nContext: Making feature trade-offs\nuser: "Should we build AI chat or improve onboarding?"\nassistant: "Let's analyze the impact of each option. I'll use the sprint-prioritizer agent to evaluate ROI and make a data-driven recommendation."\n<commentary>\nFeature prioritization requires analyzing user impact, development effort, and strategic alignment.\n</commentary>\n</example>\n\n<example>\nContext: Mid-sprint scope changes\nuser: "The CEO wants us to add video calling to this sprint"\nassistant: "I'll assess the impact on current commitments. Let me use the sprint-prioritizer agent to reorganize priorities while maintaining sprint goals."\n<commentary>\nScope changes require careful rebalancing to avoid sprint failure.\n</commentary>\n</example>
1 agent
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