Analyze unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".
日本語の概要は準備中です。原文の説明を表示しています。
anthropics/financial-services☆ 4万2026年9月22日 更新
Guide for writing the abstract of an academic economics paper. Use this skill whenever the user asks for help writing, drafting, revising, or structuring an abstract for an economics paper - whether empirical micro, development economics, applied economics, or related fields. Also trigger when the user mentions "abstract," "paper summary," or asks how to compress their findings into a short description. This skill synthesizes best practices from David Evans (CGDev), Marc Bellemare, and patterns observed in top economics journals (AER, QJE, AEJ: Applied, etc.).
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Unit economics analysis for China-focused portfolio companies. Adapted from the original unit-economics skill for Chinese business models, pricing, and market dynamics. Triggers on "A股单位经济模型", "单元经济模型", "unit economics China", "unit economics [company]", "LTV/CAC China", or "Cohort analysis [company]".
日本語の概要は準備中です。原文の説明を表示しています。
jwangkun/claude-for-financial-services-cn☆ 8342026年9月14日 更新
Unit economics analysis, CAC LTV estimation, churn inference, gross margin per unit, customer economics, subscription economics, per-unit profitability, contribution margin, payback period, cohort economics
日本語の概要は準備中です。原文の説明を表示しています。
agentii-ai/agentii-investment-intelligence☆ 2072026年9月29日 更新
Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection (e.g., 'which channel actually makes money — direct or partner?').
日本語の概要は準備中です。原文の説明を表示しています。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Guide for writing the introduction to an academic economics paper. Use this skill whenever the user asks for help writing, drafting, revising, or structuring an introduction to an economics paper - whether empirical micro, development economics, applied economics, or related fields. Also trigger when the user mentions "intro," "introduction section," "opening paragraphs," or asks how to motivate, frame, or present their research question in a paper. This skill synthesizes best practices from David Evans (CGDev), Keith Head, Claudia Sahm, Marc Bellemare, and Deirdre McCloskey.
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model", "partner economics", "RFP response", "bookings forecast", "channel mix". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).
日本語の概要は準備中です。原文の説明を表示しています。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.
日本語の概要は準備中です。原文の説明を表示しています。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Deeply analyze any empirical economics PDF using the five-question framework (五问框架): research question, identification strategy, core estimand, robustness logic, and scholarly contribution. Converts the PDF to Markdown, dispatches 5 parallel sub-agents (one per question), then compiles a 2000–3000 Chinese-character report with a transferable methodology checklist. Optimized for empirical economics papers in top journals (AER, QJE, JPE, RFS, RoF, JFE, etc.). Use this skill whenever the user wants to: - systematically analyze an empirical economics paper - apply the 五问框架 (five-question framework) to a paper - extract transferable research design elements from a top-journal paper - understand a paper's identification strategy, estimand, or robustness logic - run /five-questions, /five-q, or /paper-five-q-analysis - "帮我做五问分析", "用五问框架分析这篇论文", "analyze this paper with the five-question framework"
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Perform an exhaustive, multi-pass proofread and copy-edit of an applied-microeconomics manuscript to top-economics-journal standards (AER, QJE, Econometrica, ReStud), checking prose, equations, table notes, footnotes, and citations for avoidable errors. Use before submitting or circulating an empirical economics paper.
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Use when deciding whether a microeconomics project fits the American Economic Journal: Microeconomics (AEJ: Micro) rather than JET, GEB, Theoretical Economics, Econometrica, or AEJ: Applied. Tests scope and broad-interest fit; it does not develop the model (see aejmic-theory-model).
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Awesome-Journal-Skills☆ 1,2482026年9月27日 更新
Channel economics: design and analyze the financial structure of go-to-market channels. Use when picking a channel mix, modeling partner margin or TCO, designing partner tiers and rebates, or analyzing channel conflict.
日本語の概要は準備中です。原文の説明を表示しています。
borghei/Claude-Skills☆ 9012026年10月7日 更新
Understand essential business finance — profit margins, unit economics, cash flow, LTV/CAC, and the 4 methods to increase revenue. Use when: analyzing business profitability, making pricing decisions, evaluating SaaS unit economics, financial planning.
日本語の概要は準備中です。原文の説明を表示しています。
TerminalSkills/skills☆ 1652026年10月4日 更新
Builds depletion models with production decline, reserve replacement economics, and terminal value analysis for finite-life assets. Use when modeling depletion, analyzing resource longevity, or evaluating reserve life economics.
日本語の概要は準備中です。原文の説明を表示しています。
CaseMark/skills☆ 442026年9月9日 更新
Deconstructs unit economics with CAC, LTV, payback period, gross margin, and contribution margin analysis. Use when analyzing unit economics, validating SaaS metrics, or assessing business model efficiency.
日本語の概要は準備中です。原文の説明を表示しています。
CaseMark/skills☆ 442026年9月9日 更新
Treat tokens as a coding swarm's cost-of-goods-sold and legibility engine while accounting for finite subscription allowance when per-call price is unknown. Covers provider windows, remaining-usage evidence, burn forecasts, preemptive checkpoint/model switching, per-agent budgets, compaction, shared digests, context degradation, and spend metering. Activate on: "token budget", "context budget", "compaction strategy", "briefing as compression", "context rot", "summarization collapse", "COGS for agents", "subscription usage remaining", "five-hour or weekly limit", "burn forecast", "model switch before limit", or "/context-economics-for-agent-swarms". NOT for: memory architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory), physical containment (use sandboxed-adversarial-test-harness), or production rebodiment and fencing (use agent-resurrection-and-body-continuity).
日本語の概要は準備中です。原文の説明を表示しています。
curiositech/port-daddy☆ 22026年10月12日 更新
Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.
日本語の概要は準備中です。原文の説明を表示しています。
iOfficeAI/OfficeCLI☆ 3.2万2026年10月13日 更新
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
日本語の概要は準備中です。原文の説明を表示しています。
alirezarezvani/claude-skills☆ 2.8万2026年8月30日 更新
Evaluate SaaS unit economics and capital efficiency. Use when deciding whether the business can scale efficiently or needs correction.
日本語の概要は準備中です。原文の説明を表示しています。
deanpeters/Product-Manager-Skills☆ 7,3272026年9月2日 更新
Expert economics paper writing assistant synthesizing advice from 50+ top guides by Cochrane, McCloskey, Shapiro, Head, Bellemare, Goldin, Glaeser, Kremer, and other leading economists. USE THIS SKILL whenever the user writes, edits, reviews, rewrites, or structures any economics paper, thesis, job market paper, abstract, introduction, conclusion, results section, literature review, or referee response. Also handles LaTeX formatting, presentations, and paper audits. Covers all paper types (applied, theory, structural, mixed) and all sections.
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Activate when the user is drafting any academic economics content from scratch (e.g., outlines, abstracts, introductions, data/methods/identification sections, results narratives, conclusions, referee responses, table/figure captions) and needs economics-specific structure, phrasing options, and quality checks to produce publication-ready prose.
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation via `zepid` / hand-rolled `pandas`, IPTW + g-formula + TMLE doubly-robust triplet via `zepid` / `econml` / `lifelines`, Mendelian randomization via `pymr` / `mrtool` (or `rpy2` → `MendelianRandomization`/`TwoSampleMR`), KM / AFT / Cox survival via `lifelines`, E-value sensitivity, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `econml.dml` / `doubleml`, S/T/X/R/DR meta-learners via `econml.metalearners` / `causalml`, causal forest via `econml.grf` / `causalml`, Dragonnet / TARNet / CEVAE neural causal via `causalml`, BCF via `pymc-bart` / `bcf-py`, matrix completion, CATE distribution + policy tree via `econml.policy` / `policytree-py`, off-policy evaluation, conformal causal via `mapie`, fairness audit via `fairlearn`, DAG learning via `causal-learn` / `cdt` / LLM-assisted). Prescribes which library to reach for at each step, shows the canonical code, and links to deeper `references/` files for variant-specific patterns. Use when the user asks for a **complete empirical analysis** in Python, wants to replicate an applied-economics paper from scratch, needs a reproducible workflow that is NOT opinionated on any single vertical package (contrast with StatsPAI), wants explicit control over every estimator and diagnostic, or asks "how do I write a full empirical pipeline in Python?". Also triggers when the user names a specific classical step in isolation — "winsorize at 1/99%", "run Breusch-Pagan", "build a Table 1 balance table", "do a placebo test", "event study plot", "mediation analysis" — and wants it wired into the broader pipeline. Mode A triggers on "target trial emulation", "IPTW", "TMLE", "Mendelian randomization", "STROBE", "公共健康", "流行病学". Mode B triggers on "DML", "double machine learning", "causal forest", "meta-learner", "Dragonnet", "BCF", "policy tree", "conformal causal", "fairness audit", "因果机器学习".
日本語の概要は準備中です。原文の説明を表示しています。
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4,5992026年10月12日 更新
Use when evaluating business model viability, analyzing profitability per customer/product/transaction, validating startup metrics (CAC, LTV, payback period), making pricing decisions, assessing scalability, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, break-even analysis, or needs to determine if a business can be profitable at scale.
日本語の概要は準備中です。原文の説明を表示しています。
MaxMiksa/Auto-Company☆ 3,1282026年10月4日 更新
Owns the financial position: planning, budgeting, forecasting, unit economics, cash, and the numbers the business is run and reported on. Use this to build or challenge a budget, model a decision's financial consequence, assess unit economics or runway, evaluate an investment or spend request, set financial controls, or when a plan's numbers do not reconcile. Also use to decide whether the business can afford something.
日本語の概要は準備中です。原文の説明を表示しています。
cbrock84/headcount☆ 2,0422026年9月18日 更新