documents

Use Paul Graham's "Startup = Growth" framework as an operational decision tool. Computes weekly growth rates, benchmarks against YC tiers (1% concerning, 5-7% good, 10%+ exceptional), projects compound growth over time, and frames every startup decision through the question "does this serve your target growth rate?" Ships a deterministic CLI calculator. Load when founders ask about growth rate, weekly growth, startup traction, metrics, or whether they're moving fast enough; do not use for general financial modeling or engineering work unrelated to growth metrics.

Query the Open Library catalog from the terminal: search books and authors, look up works, editions, and ISBNs, enumerate every edition of a work, read community ratings, and resolve cover-image URLs. Fully keyless public API. Includes the OL…M/W/A key-graph reference, ISBN 302-redirect resolution, search query syntax, covers-host rules, and worked pipelines. Do not use for library-IT administration (Koha/MARC/ILS migration), commercial book-data feeds, or managing your reading account on Open Library itself.

Translate privacy principles and legal requirements into data-flow, lifecycle, acceptance, and verification artifacts. Map data classification, purpose, processing, access, retention, deletion, residency, and consent; define verifiable privacy acceptance criteria; and produce data-lifecycle records, retention/deletion verification plans, and privacy change reviews. Use when engineering privacy into a system, feature, or data flow — not for legal advice, jurisdiction-specific regulatory interpretation, or replacing security engineering or incident response.

Discover and compare Trakt.tv trending, popular, and anticipated movies and shows from the terminal. Do not use this skill for TMDb catalog metadata, credits, images, or provider lookups; use the tmdb skill for those tasks.

Design, govern, document, review, and evolve consumer-facing APIs and event interfaces. Use when choosing REST/HTTP, GraphQL, RPC, events, webhooks, or streaming; writing OpenAPI or AsyncAPI contracts; assessing an API landscape, ownership, duplication, lifecycle, discoverability, retirement, gateways, service meshes, north-south or east-west traffic, routing, policy, observability, or failure boundaries; defining schemas, pagination, mutations, errors, idempotency, or compatibility; or planning versioning, deprecation, and migration. Do not use for product discovery, platform operations, full security assessment, ADR authoring, or delivery gates; route those to the neighboring specialist skills.

Use for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research methodology, or data science project leadership. Load when the user asks about statistical methods, experimental design, model selection, A/B testing, hypothesis testing, power analysis, regression, causality, Bayesian analysis, or research methodology. For insurance, actuarial, claims, reserving, solvency, credibility, tail-risk, or financial-risk statistical modeling, use `actuarial-risk-modeling`; for deterministic operating and SaaS financial models, use `financial-modeling`.

Run end-to-end product experiments from assumption to decision: translate assumptions into testable hypotheses and experiment briefs, select the right method among qualitative interviews, prototypes, concierge tests, fake doors, feature flags, and A/B tests, and produce readouts that update the roadmap and decision record. Do not use when a qualitative or prototype test is the clearly right answer without statistical measurement; do not prescribe A/B testing by default; do not treat statistical significance as the only decision criterion or hide ethical and guardrail considerations.

Guide embedded technical engagements from ambiguous stakeholder need through discovery, framing, hypothesis, build, evaluation, deployment, adoption, measurement, and generalization while preserving evidence, decision rights, and field learning. Use when one accountable technical lead must carry continuity across customer or stakeholder discovery, implementation, production fit, adoption, and measurable outcomes. Do not use for a bounded repository change, product investment governance, ongoing reliability or platform ownership, an isolated specialist task, or advisory work that ends before implementation and adoption.

Build multi-agent AI systems with LangGraph — the low-level orchestration framework for stateful, graph-based agent workflows. Covers supervisor, swarm, and hierarchical multi-agent patterns; subgraph composition; state management (checkpointers/stores); persistence; evals; and production debugging. Reach for this when designing agent architectures that need cycles, conditional branching, parallel execution, or human-in-the-loop patterns.

Apply distilled coding principles from 14 classic software books to code review, refactoring, design, and implementation decisions. Do not use for language- or framework-specific tutorials, tool manuals, or tasks already governed by a project's established conventions.