Claude Code: AI Agent Workflow Collection

SaaS financial modeling engine that generates unit economics models, feature ROI calculators, pricing scenario analyses, TAM/SAM/SOM sizing, build-vs-buy comparisons, and revenue projections from natural language inputs. Use when building business cases, calculating LTV/CAC/payback, modeling pricing changes, estimating feature revenue impact, running sensitivity analyses, or preparing financial justifications for product investments. Produces actual calculations with explicit assumptions and sensitivity ranges.

Strategic product decision engine that reads ALL available project context (PRDs, research docs, metrics, competitive intel, roadmaps, CLAUDE.md) and provides holistic, multi-dimensional strategic recommendations. Use when making product prioritization decisions, quarterly planning, evaluating build/ship/kill tradeoffs, resolving conflicting stakeholder input, determining what to build next, or any strategic question requiring synthesis across multiple information sources.

Create an AI Product Strategy Pack (thesis, prioritized use cases, system plan, eval + learning plan, agentic safety plan, roadmap). Use for AI product strategy, LLM/agent strategy, AI roadmap, AI-first product direction.

Multi-audience communication multiplexer. Takes ONE product update, decision, or launch plan and generates 5 perfectly tailored versions for different stakeholders (engineering, executive, board, customer, sales) simultaneously.

Builds a Blue Ocean Strategy Canvas with the as-is competitive value curve, the Eliminate-Reduce-Raise-Create (ERRC) grid, the to-be value curve, and a non-customer analysis to find uncontested market space. Use when an industry is commoditizing, when differentiating against an entrenched incumbent, when designing a new category, or when reframing strategy around buyer utility instead of feature parity.

Models cash burn, runway, and scenario-based cash flow with explicit triggers, default-alive versus default-dead diagnosis, and a 13-week rolling forecast. Use when planning a fundraise, deciding on layoffs, evaluating hiring plans, modeling a downturn, presenting cash position to the board, or pressure-testing a Chief Financial Officer (CFO) operating plan.

Ranks competing investments using Net Present Value (NPV), Internal Rate of Return (IRR), payback period, Profitability Index (PI), and strategic option value - then produces a portfolio-level recommendation. Use when evaluating capital expenditure requests, comparing Mergers and Acquisitions (M&A) targets, sizing Research and Development (R&D) bets, prioritizing engineering investments, sun-setting initiatives, or preparing a board capital allocation memo.

Connects Figma design components to code components using Code Connect. Use when user says "code connect", "connect this component to code", "connect Figma to code", "map this component", "link component to code", "create code connect mapping", "add code connect", "connect design to code", or wants to establish mappings between Figma designs and code implementations. Requires Figma MCP server connection.

Models multi-round competitive interactions: who reacts, how fast, with what move, and what payoff outcome - using reaction functions, commitment value, and signaling theory. Use when planning a pricing change, market entry, product launch, capacity addition, or any move where competitor reaction will determine whether the move pays off.

Generates custom design system rules for the user's codebase.

Synthesizes raw customer interview transcripts into themes, quotes, Jobs-to-be-Done (JTBD) signals, force-of-progress diagrams, and actionable opportunity hypotheses with confidence levels. Use after a round of discovery, switching, win-loss, or churn interviews; when preparing a research readout; when aligning a team on what the customer signal actually says; or when feeding inputs into an Opportunity Solution Tree (OST).

Builds a transparent Discounted Cash Flow (DCF) valuation with a 5-10 year forecast, terminal value, Weighted Average Cost of Capital (WACC) derivation, sensitivity tables, and a football-field summary. Use when valuing a company, business unit, acquisition target, or capital project; pressure-testing an investment thesis; preparing a board valuation memo; or stress-testing assumptions against precedent transactions and trading comparables.

Performs structured fundamental analysis of annual reports (Form 10-K, Form 10-Q): ratio analysis, quality of earnings, working-capital efficiency, segment decomposition, accounting red flags, and Management's Discussion and Analysis (MD&A) parsing. Use when underwriting an investment, evaluating a competitor, preparing for an earnings call, building peer comparables, or screening for accounting risk.

Extracts Jobs-to-be-Done (JTBD) statements (functional, emotional, social) from raw research - interviews, surveys, support tickets, sales calls - and produces a job map with progress measures and outcome statements. Use when reframing a product around customer outcomes, segmenting beyond demographics, building a competitive switching analysis, prioritizing features, or aligning product, marketing, and sales on the same job.

Estimate market size using TAM, SAM, and SOM with top-down and bottom-up approaches. Use when sizing a market opportunity, estimating addressable market, preparing for investor pitches, or evaluating market entry.

Designs auctions, matching mechanisms, pricing schemes, and incentive structures using mechanism-design principles - Incentive Compatibility (IC), Individual Rationality (IR), revenue equivalence, and budget balance. Use when designing a marketplace pricing model, a referral program, an internal resource allocation, a Request for Proposal (RFP) or procurement process, an auction format, or any allocation rule where participants act strategically.

Models a strategic interaction as a normal-form (or extensive-form) game, identifies pure-strategy and mixed-strategy Nash equilibria, applies dominance and iterated elimination, checks subgame perfection, and translates the equilibrium back into a recommended action. Use when analyzing pricing wars, capacity decisions, market entry, bidding strategy, negotiation dynamics, or any two-or-more party interaction where each player's best move depends on what others do.

Prepares for a negotiation using the Best Alternative to a Negotiated Agreement (BATNA), reservation price, Zone of Possible Agreement (ZOPA), multi-issue trade design, anchoring tactics, and concession plans, then simulates the counterparty and produces a play-by-play strategy. Use before commercial negotiations, Mergers and Acquisitions (M&A) talks, vendor or partnership deals, internal resource negotiations, hiring offers, or any multi-issue bargaining where preparation outranks instinct.

Cascades strategy into Objectives and Key Results (OKRs) across company, function, and team levels with explicit alignment, leading versus lagging indicators, scoring conventions, and a quarterly review ritual. Use when designing OKRs from scratch, fixing a broken OKR program, aligning company-level strategy to team-level execution, training a new team on OKR mechanics, or preparing a quarterly OKR review.

Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.

Performs a rigorous Porter's Five Forces analysis: industry structure, supplier power, buyer power, threat of new entrants, substitutes, and rivalry intensity, with quantified pressure scoring and a strategic-positioning recommendation. Use when entering a new market, defending an existing position, evaluating an industry's structural attractiveness, advising on Mergers and Acquisitions (M&A) in a new vertical, or preparing a competitive strategy memo.

Analyze pricing strategy with competitive positioning, packaging, and revenue modeling. Use when: analyze pricing strategy, pricing strategy, analyze pricing, pricing analysis, evaluate pricing.

Coaches a product trio through continuous product discovery: weekly customer touchpoints, assumption mapping, story mapping, and the discovery / delivery dual-track cadence. Use when standing up a discovery practice from scratch, debugging why discovery isn't sticking, training a new product manager on continuous discovery, or designing a quarterly discovery plan around an outcome.

Runs candidate features through Reach-Impact-Confidence-Effort (RICE), Kano, Must-Should-Could-Won't (MoSCoW), and Cost-of-Delay scoring, surfaces convergence and divergence across frameworks, and produces a defensible quarterly priority list with explicit trade-offs. Use when building a quarterly or annual roadmap, resolving conflicting stakeholder input, justifying a deprioritization to a stakeholder, or normalizing requests from multiple sources (sales, customer success, leadership) into one queue.