Claude Skills by The-Utopia-Studio

When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' 'viral content,' 'what should I post,' 'repurpose this content,' 'tweet ideas,' 'LinkedIn carousel,' 'social media strategy,' or 'grow my following.' Use this for any social media content creation, repur...

Use this skill when a rep wants warm intro paths into a target prospect \u2014 \\\"Find warm intro paths for [company]\\\", \\\"Who do we know at [company]?\\\", \\\"Can anyone intro me to [role] at [company]?\\\", \\\"Warm intro - [company]\\\". Surfaces the strongest available warm intro paths from your company's relationship network \u2014 employees, customers, partners, investors, advisors, call transcripts \u2014 with honest, evidence-based confidence labels. Decision support only: never...

Run technical due diligence as Ada — The Utopia Studio's DD analyst. Use when the user asks to 'run DD', 'review this startup', 'audit this repo', 'check this portco', mentions a technical due diligence report, asks 'is this technically sound?', or says 'run DD on [company]'. Ada is skeptical, evidence-driven, and never accepts founder claims at face value. She composes repo-scanner, security-auditor, devops-advisor, cost-optimizer, integration-linker, and technical-dd into a structured 5-pha...

Produces a Bayesian prior probability that an offered transaction is +EV for the recipient, given that the counterparty chose to propose it. Applies Akerlof market-for-lemons logic -- if they offered it, they believe it is +EV for them, so the prior that it is +EV for us is materially below 50%. Reusable across trade evaluation, waiver drops (another team dropping a player is also adverse selection), job-offer analysis, M&A, and any "someone offered me this" situation. Use when you receive an...

Computes the optimal shaded bid for a first-price sealed-bid auction given a true private value, an estimate of the number of competing bidders N, and a value-distribution assumption. Implements the `(N-1)/N` equilibrium shading rule for uniform private values, adjusts for log-normal or empirical value distributions, layers a risk-aversion adjustment, and caps output against the bidder's remaining budget. Domain-neutral auction theory reusable across fantasy sports (baseball FAAB, NBA/NHL wai...

Applies a Bayesian haircut to a bid valuation for common-value auctions where winning is itself evidence the bidder over-estimated. Takes a raw valuation, a value-type classification (common_value / private_value / mixed), the number of informed bidders N, and a signal-dispersion estimate, and returns an adjusted valuation. Domain-neutral and reusable across fantasy FAAB, prediction markets, M&A bids, ad-auction budgets, and any generic bidding context. Use when user mentions "winner's curse"...

Applies Bayesian reasoning to systematically update probability estimates with new evidence, helping make better forecasts and avoid overconfidence. Use when making predictions or judgments under uncertainty, forecasting outcomes, evaluating probabilities, testing hypotheses, calibrating confidence, assessing risks with uncertain data, or when user mentions priors, likelihoods, Bayes theorem, probability updates, forecasting, calibration, or belief revision.

Analyzes a company's debt-equity mix and determines the optimal capital structure that minimizes WACC. Computes WACC at each debt ratio from 0% to 90%, identifies the minimum, and recommends whether to add or reduce debt with specific debt type matching (maturity, currency, fixed vs floating). Use when analyzing capital structure, optimizing debt levels, evaluating leverage, or when user mentions optimal debt ratio, capital structure, leverage optimization, debt capacity, or recapitalization.

Systematically investigates causal relationships to identify true root causes rather than correlations or symptoms. Distinguishes genuine causation from spurious associations, tests competing explanations, and designs interventions addressing underlying drivers. Use when investigating why something happened, debugging systems, analyzing failures, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"

Clean up messy spreadsheet data — trim whitespace, fix inconsistent casing, convert numbers-stored-as-text, standardize dates, remove duplicates, and flag mixed-type columns. Use when data is messy, inconsistent, or needs prep before analysis. Triggers on "clean this data", "clean up this sheet", "normalize this data", "fix formatting", "dedupe", "standardize this column", "this data is messy".

Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without compa...

Computes cost of equity (CAPM), cost of debt (synthetic rating), and weighted average cost of capital (WACC) for any company in any currency. Handles emerging market risk premiums, bottom-up beta estimation, and multi-country operations. Use when estimating discount rates, computing WACC, determining hurdle rates, analyzing cost of equity or debt, or when user mentions cost of capital, WACC, beta, equity risk premium, country risk premium, or discount rate.

Challenges plans, designs, and decisions from multiple adversarial perspectives to surface blind spots, hidden assumptions, and vulnerabilities before they cause real damage. Use when testing plans or decisions for blind spots, need adversarial review before launch, validating strategy against worst-case scenarios, building consensus through structured debate, identifying attack vectors or vulnerabilities, or when groupthink or confirmation bias may be hiding risks.

Generates structured experimental designs (factorial, response surface, Taguchi) to systematically discover how multiple factors affect outcomes while minimizing experimental runs. Use when optimizing multi-factor systems with limited experimental budget, screening many variables to find the vital few, discovering interactions between parameters, mapping response surfaces for peak performance, validating robustness to noise factors, or when users mention factorial designs, A/B/n testing, para...

Monitors external trends across PESTLE dimensions, detects weak signals of emerging change, develops scenario-based futures, and sets adaptive signposts for early warning. Use when scanning external trends for strategic planning, detecting early indicators of change, planning scenarios for multiple futures, setting signposts and indicators for early warning, or when user mentions environmental scanning, horizon scanning, trend analysis, scenario planning, strategic foresight, or futures think...

Decomposes complex unknowns into estimable components to produce rapid order-of-magnitude answers with bounded uncertainty. Use when making quick estimates (market sizing, resource planning, feasibility checks), bounding unknowns with upper/lower limits, sanity-checking strategic assumptions, or when user mentions Fermi estimation, back-of-envelope calculation, order of magnitude, ballpark estimate, or triangulation.

Calculates probability-weighted averages of all possible outcomes to enable rational decisions under uncertainty. Covers scenario identification, probability estimation, payoff quantification, and risk-adjusted interpretation. Use when comparing risky options (investments, product bets, strategic choices), prioritizing projects by expected return, assessing whether to take a gamble, or when user mentions expected value, EV calculation, risk-adjusted return, probability-weighted outcomes, or d...

Stress-tests predictions by assuming failure and working backward to identify blind spots, tail risks, and overconfidence. Applies Gary Klein's premortem technique to probabilistic forecasting. Use when confidence is high (>80% or <20%), need to identify tail risks and unknown unknowns, want to widen overconfident intervals, or when user mentions premortem, backcasting, what could go wrong, stress test, or black swans.

Generate a polished one-page PowerPoint slide summarizing key takeaways from recent funding rounds and notable capital markets activity across a user's watched sectors or companies. Use this skill when the user asks for a deal flow summary, weekly recap, funding digest, transaction roundup, or capital markets briefing. Triggers on: 'deal flow digest', 'weekly funding recap', 'deal roundup', 'transaction summary this week', 'what happened in [sector] this week', 'capital markets update', or an...

Applies "what if" thinking to explore alternative scenarios, test assumptions, understand causal relationships, and prepare for uncertainty. Guides through counterfactual reasoning, scenario exploration, pre-mortem analysis, and stress testing decisions against alternative futures. Use when exploring alternative scenarios, testing assumptions through "what if" questions, understanding causal relationships, conducting pre-mortem analysis, stress testing decisions, or when user mentions counter...

Populates investment banking pitch deck templates with data from source files. Use when: user provides a PowerPoint template to fill in, user has source data (Excel/CSV) to populate into slides, user mentions populating or filling a pitch deck template, or user needs to transfer data into existing slide layouts. Not for creating presentations from scratch.

Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.

Performs discounted cash flow valuation using the appropriate model variant (DDM, FCFE, or FCFF) with configurable growth stages. Produces year-by-year cash flow projections, terminal value, equity bridge (subtract debt, add cash, subtract option value), per-share intrinsic value, and sensitivity analysis. Use when valuing a company intrinsically, building a DCF model, estimating fair value, or when user mentions DCF, discounted cash flow, intrinsic value, terminal value, or free cash flow va...

Build investor-ready pitch decks as Khalil — The Utopia Studio's deck builder. Use when the user asks to 'build a deck', 'turn these notes into slides', 'pitch deck from these notes', 'investor presentation', 'syndication deck', 'co-investor deck', 'help [portco] with their deck', or shares founder meeting notes and wants a deck. Khalil is storytelling-first, audience-obsessed, and brand-disciplined. He always asks who's reading the deck before drafting. He composes business-narrative-builder...

Establishes pre-defined, objective conditions for stopping projects and specific decision points for continue/pivot/kill evaluations. Guides through defining kill criteria, setting go/no-go gates, avoiding sunk cost fallacy, and executing disciplined stopping decisions. Use when defining stopping rules for projects, avoiding sunk cost fallacy, setting objective exit criteria, deciding whether to continue/pivot/kill initiatives, or when users mention kill criteria, exit ramps, stopping rules, ...

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.

Build a responsive, interactive pitch-deck website from a brand book + a PRD/example deck. Use when the user asks to "build a pitch deck", "make an investor deck", "create a sales deck", generate a deck site from a brand book, or scaffold a deck from a PRD or existing slides. Pulls brand tokens (colors, typography, voice) from a brandbook-builder-style repo, runs a guided brief (investor vs sales, copy approval, image/logo intake, reference mining), then scaffolds a Vite + React + TS + Tailwi...

Generate investor-ready pitch decks as branded PPTX files from founder meeting notes, uploaded decks, DD reports, and strategy docs. Use this skill whenever the user mentions building a pitch deck, turning notes into slides, creating an investor deck, preparing for a co-investor presentation, or helping a portfolio company with their deck. Also trigger when the user uploads Granola meeting notes, founder call transcripts, or company materials and asks for a deck, slides, or presentation for i...

Anchors predictions in historical reality by identifying a class of similar past events and using their statistical frequency as a baseline (outside view) before analyzing case-specific details. Use when starting a forecast, establishing base rates, testing "this time is different" claims, or when user mentions reference classes, outside view, base rates, or starting a new prediction.

Values a company relative to comparable firms using price multiples (PE, PBV, EV/EBITDA, EV/Sales). Implements the four-step framework (define, describe, analyze, apply) with both simple peer comparison and sector regression approaches. Use when valuing a company relative to peers, analyzing multiples, selecting comparable companies, or when user mentions PE ratio, EV/EBITDA, relative valuation, comparable companies, trading multiples, or price-to-book.

Systematically evaluates claims by triangulating sources, rating evidence quality (primary/secondary/tertiary), assessing source credibility, and reaching confidence-rated conclusions to prevent confirmation bias and reliance on unreliable sources. Use when verifying claims before decisions, fact-checking statements, conducting due diligence, evaluating conflicting evidence, or when user mentions "fact-check", "verify this", "is this true", "evaluate sources", "conflicting evidence", or "due ...

Detects and removes cognitive biases from reasoning using Julia Galef's Scout Mindset framework. Provides reversal tests, scope sensitivity checks, status quo bias tests, confidence interval audits, and full bias audits. Use when a prediction feels emotional, stuck at 50/50, or when validating forecasting process. Use when user mentions scout mindset, soldier mindset, bias check, reversal test, scope sensitivity, or cognitive distortions.

Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise sin...

Generate investment-grade Technical Due Diligence reports for The Studio (Utopia Capital). Use this skill whenever the user mentions technical due diligence, TDD, tech DD, technical assessment, technical evaluation of a company, or wants to assess whether a startup's technology works, is well-built, can scale, and what the technical risks are. Also trigger when the user uploads company materials (pitch decks, technical docs, corporate profiles) and asks for a due diligence analysis, technical...

Synthesizes intrinsic (DCF) and relative (multiples) valuation outputs into a final value estimate and investment recommendation. Reconciles divergent valuations, reverse-engineers what the market is pricing in (implied growth, implied ROIC), computes margin of safety, and produces a buy/sell/hold recommendation with catalysts. Use when combining multiple valuation approaches, making investment recommendations, reconciling DCF with multiples, or when user mentions reconcile valuations, invest...

Given a current win probability and a downside asymmetry flag, recommends a variance-seeking, neutral, or variance-minimizing posture and emits a numeric multiplier (typically 0.8-1.3) for downstream consumers to apply to boom-bust scores, position sizes, or bet sizes. Favorites minimize variance; underdogs maximize it. Reusable across fantasy sports lineup construction, portfolio allocation, poker bankroll decisions, racing strategy, and any decision where the agent controls a variance knob....

Fires when a fellow proposes bringing an external/market skill into the studio repo — "found a skill for X on skills.sh", "should we add this market skill", "ingest the good parts of <repo/skill>", "there's a public skill that does Y", "pull this skill in", "vet this skill from the ecosystem". Produces an Ingestion Decision Record plus a FOLD / SUPERSEDE / REJECT / ADD-NEW decision and the concrete diff into an existing studio skill. NOT for authoring a brand-new proprietary skill from scratc...

Runbook for having an AGENT run a real task end to end, to measure the automation frontier (which steps it does unaided vs which need a human) and the cost-per-outcome to the cent (input+output tokens + tool calls + human-fix minutes, all priced). Fires on "agent does the task", "measure cost per outcome", "agent concierge", "automation frontier", "price it to the cent", "what can the agent not do unaided". Output: a cost-per-outcome read with the full breakdown, plus a frontier map. Not prob...

Fires when a fellow is designing ONE production agent and asks what it should be built from — "design an agent for X", "what tools and memory does this agent need", "spec the agent", "our agent isn't getting smarter / never remembers corrections — how do we build its memory". Returns a four-part agent spec — role (one owned decision) · tools (the commodity shell) · memory layer (CLAUDE.md · skills · lessons.md · trace archive, loaded at birth) · eval — where the memory layer is the only part ...

A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.

When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products.

Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.

Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.

Amplify safe or boring designs to make them more visually interesting and stimulating. Increases impact while maintaining usability. Use when the user says the design looks bland, generic, too safe, lacks personality, or wants more visual impact and character.

Builds the magnitude of an opportunity from the smallest countable units up, with every multiplier and its source shown in the open, and permits a top-down TAM only at the end as a labelled sanity check. Fires on "size this bottom-up", "build the number", "don't give me a TAM", "how big is this really, show me the arithmetic", "what's the total from the units up", or when a fellow has a per-unit value and wants a total market magnitude they can defend line by line. Outputs a filled bottom-up ...

Add strategic color to features that are too monochromatic or lack visual interest, making interfaces more engaging and expressive. Use when the user mentions the design looking gray, dull, lacking warmth, needing more color, or wanting a more vibrant or expressive palette.

Fires when a fellow is ready to design how the AI product is actually built — "architect the product", "how do we build the AI system", "design the AI system", "what's the system architecture", "what does the stack look like". Returns a compound-system architecture (input → router → retrieve/reason/act → validate & guardrails → output over a data layer), a 40/20/30/10 effort-allocation plan, and named model-swap points, then kills any monolithic one-big-prompt design. Do NOT fire to write the...

First-contact teardown of a raw product idea. Fires when a fellow says "here's my idea", "tear this apart", "rip this concept apart", "what am I missing", or "what should I build first". Convenes five adversarial lenses, names the one load-bearing gap, and returns a Gap Map plus one First-Probe Brief costing under a week. NOT for an already-scoped concept you want stress-tested against the five so-whats (use so-what-stress-test) or scored numerically across eight dimensions (use problem-quali...

Runbook for delivering a product outcome by hand, as the founder, to ONE real customer — to test willingness to pay and the real workflow including the exceptions that break automation. Fires on "do it by hand first", "concierge test", "concierge MVP", "deliver it manually", "founder-delivered version before we automate". Output: a concierge log plus a willingness-to-pay signal scored on the evidence ladder (money charged 1.0 beats a verbal yes 0.3). Not probe-matrix (that picks which probe);...

Stands up ONE living opportunity tree fed by three live inputs and keeps it current after launch. Fires when a fellow says "set up discovery", "continuous discovery", "opportunity tree", "keep learning after launch", or "discovery after launch". Returns an opportunity tree (outcome → opportunities → solutions → tests) wired to customer interviews, production traces, and eval telemetry — each feed stamped with its evidence rung, its cadence, and a named synthesis owner. NOT for scoring one sig...