statistical-problem-formulation
Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
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Formulate statistical research problems with formal notation, target parameters, assumptions, hypotheses, evaluation criteria, and theory targets.
Analyze theoretical properties of statistical methods under the formal formulation: identifiability, bias, variance, consistency, asymptotics, coverage, error bounds, robustness, and limitations.
Design statistical methods, baselines, diagnostics, variants, and ablations that directly address a formal problem formulation.
Use this skill to get documentation for third-party APIs, SDKs or libraries before writing code that uses them to ensure you have the latest, most accurate documentation. This is a better way to find documentation than doing web search. This includes when a user asks for tasks like "use the OpenAI API", "call the Stripe API", "use the Anthropic SDK", "query Pinecone", or any other time the user asks you to write code against an external service and you need current API reference. Fetch the docs with chub before answering, rather than relying on your pre-trained knowledge, which may be outdated because of recent changes to these APIs. Be sure to use this skill when the user asks for the latest docs, latest API behavior, or explicitly mentions chub or Context Hub. Ensure `chub` is available, run `chub --help`, then follow the instructions there.
AI-powered web search via Exa with content extraction. Use when user says "exa search", "web search with content", "find similar pages", or needs broad web results beyond academic databases (arXiv, Semantic Scholar).
Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow.
Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.
Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.
AI Berkshire skill: 行业投资研究:产业链全景扫描 + 四大师个股分析框架. Source: skills/industry-research.md.
This skill should be used when the user asks "how-to" or factual questions about Nightingale (n9e) — UI/where-to-click, business groups/subscription rules/mute rules/edge mode, Token usage, notification pipeline, self-healing trigger conditions; OR about categraf input plugin field meanings, metric names, defaults, environment variables, config syntax (e.g. "how to write [[instances]]", "unit of ping_average_response_ms"). NOT for actively troubleshooting an alert or querying metrics.