Claude Skills by majiayu000

This skill group covers electrostatic potential analysis from first-principles

Use when seeking analogous solutions from other domains, when stuck on a problem and need fresh perspectives, or when evaluating whether approaches from field X might apply to field Y. Requires structured problem statement.

Use when seeking analogous solutions from other domains, when stuck on a problem and need fresh perspectives, or when evaluating whether approaches from field X might apply to field Y. Requires structured problem statement.

Calculates statistical power and minimum sample sizes for RNA-seq, ATAC-seq, and other sequencing experiments. Use when planning experiments, determining how many replicates are needed, or assessing whether a study is adequately powered to detect expected effect sizes.

Analyze experiment results and generate discussion paragraphs for academic papers. Two-phase workflow: identify measurable findings (Phase 1), confirm with user, then generate grounded discussion paragraphs (Phase 2). Accepts tables, statistics, or result descriptions. 实验分析与讨论段落生成。

Search academic literature via Semantic Scholar MCP, select papers interactively, and generate verified BibTeX entries. 文献检索与BibTeX生成，通过Semantic Scholar MCP。

Verify logical consistency across paper sections. Traces argument chains and identifies gaps, unsupported claims, terminology inconsistencies, and number contradictions. 论文逻辑验证，识别论证链断裂、无支撑声明、术语不一致、数字矛盾。

Simulate peer review of academic papers with structured feedback. Produces bilingual review report with scoring and actionable suggestions. Triggers on "review", "peer review", "simulate reviewer", "审稿", "模拟评审".

Recommend appropriate chart types for experimental data with rationale and tool hints. Geography-aware: choropleth, spatial scatter, kernel density when spatial data detected. 为实验数据推荐合适的图表类型，支持地理空间数据可视化建议。

Fetches and classifies PR review feedback with context isolation. Returns structured JSON with thread IDs for deterministic resolution. Use when analyzing PR comments before addressing them.

Review a pull request or contribution deeply, explain it tutorial-style for a maintainer, and produce a polished report artifact such as HTML or Markdown. Use when asked to analyze a PR, explain a contributor's design decisions, compare it with similar systems, or prepare a merge recommendation.

Research an upstream repo.

Research an upstream repo.

Learn from PR outcomes.

Learn from PR outcomes.

Analyze PR review comments from a GitHub PR URL. Fetch review comments, verify each finding against the actual codebase, assess validity (correct/incorrect/partial), and present a structured summary with recommended actions. Use when given a PR review URL or when asked to check/analyze PR feedback.

Practitioner methodology for longitudinal case study research, evidence-based documentation, and publication-ready academic writing in AI-assisted development.

Practitioner methodology for longitudinal case study research, evidence-based documentation, and publication-ready academic writing in AI-assisted development.

Use before starting implementation - research repository documentation, codebase patterns, and external resources to inform the approach

Retrieves and processes AORC precipitation data for HEC-RAS/HMS models. Handles spatial averaging over watersheds, temporal aggregation, DSS export, and Atlas 14 design storms. Use when working with historical precipitation, AORC data, calibration workflows, design storm generation, rainfall analysis, SCS Type II distributions, AEP events, 100-year storms, or generating precipitation boundary conditions for rain-on-grid models. Triggers: precipitation, AORC, Atlas 14, design storm, rainfall, ...

Analyze spatial variability of NOAA Atlas 14 precipitation frequency estimates within HEC-RAS model domains using intelligent extent-based downloading. Helps determine whether uniform rainfall assumptions are appropriate for rain-on-grid modeling by calculating min/max/mean/range statistics within 2D flow areas or project extents. Uses NOAA CONUS NetCDF with HTTP byte-range requests for 99.9% data reduction compared to traditional state-level ZIP downloads. Primary sources: - ras_commander...

Track and evaluate AI predictions over time to assess accuracy. Use when reviewing past predictions to determine if they came true, failed, or remain uncertain.

Analyze what could go wrong with a plan. Use when: - User asks "what could go wrong", "risks", "potential issues" - Before implementing a significant change - User wants to validate an approach - Planning a risky operation

Identify failure modes before they occur. Use when reviewing plans, designs, or PRs to catch risks early. Not for post-incident analysis or debugging active issues.

Debug preprocessing pipeline failures. Guides through reading checkpoint files, checking step artifacts, interpreting QC metrics, examining visualization PNGs, and identifying which step failed and why. Use when a preprocessing run produces unexpected results, crashes, or generates poor-quality outputs.

When the user wants decision support systems, recommendation engines, or prescriptive analytics. Also use when the user mentions "decision optimization," "recommendation system," "what should we do," "action recommendations," "decision support," "intelligent recommendations," "automated decisions," or "prescriptive models." For pure optimization, see optimization-modeling. For forecasting, see demand-forecasting.

Structures equity option pricing with Black-Scholes, binomial models, and implied volatility analysis. Use when pricing options, calculating Greeks, or analyzing implied volatility.

Pricing Research is a sophisticated analytical skill designed to systematically investigate price-related questions including customer price sensitivity, competitive pricing dynamics, optimal price points, value perception, and pricing strategy effectiveness.

Get a general understanding of the codebase (stack, key files, structure, etc) and/or specific feature

Discover how a codebase already handles a specific concern — search broadly, find every instance, and assess consistency. The "how does this app do X?" tool.

曲を設計視点で分析し、analysis/{slug}.mdに保存。曲の本質、構造、コード進行、アレンジメントを言語化する。

Mathematical foundations of uncertainty and random phenomena. Covers sample spaces, events, axioms, conditional probability, Bayes' theorem, independence, random variables, distributions (discrete and continuous), expected value, variance, the law of large numbers, and the central limit theorem. Use when computing probabilities, reasoning about random events, working with probability distributions, or building the foundation for statistical inference.

Use when beginning analytical or strategic tasks, facing undefined problems, or facing analysis paralysis—requires explicit problem definition before proceeding.

Мета-фреймворк структурированного решения любых задач. Определяет область знаний, находит существующие фреймворки через web research, валидирует подходы, выявляет типичные ошибки и constraints. ОБЯЗАТЕЛЬНО использует sequential thinking и web research на каждом запуске. Активировать только при явном запросе пользователя на "problem-framing", "фрейминг задачи" или "структурированный анализ задачи".

Мета-фреймворк структурированного решения любых задач. Определяет область знаний, находит существующие фреймворки через web research, валидирует подходы, выявляет типичные ошибки и constraints. ОБЯЗАТЕЛЬНО использует sequential thinking и web research на каждом запуске. Активировать только при явном запросе пользователя на "problem-framing", "фрейминг задачи" или "структурированный анализ задачи".

Use when 需要讨论方案权衡/架构选型/需求澄清，且目标/约束/成功标准不清或存在多解权衡时。

Use when 需要讨论方案权衡/架构选型/需求澄清，且目标/约束/成功标准不清或存在多解权衡时。

Apply systematic problem-solving techniques for complexity spirals (simplification

Use when stuck, facing a complex bug, or need root cause analysis — 5 whys, bisection, inversion techniques

(ePost) Use when stuck, facing a complex bug, or need root cause analysis — 5 whys, bisection, inversion techniques

Review process health and bottlenecks

Map workflows, extract SOPs, and identify automation opportunities through systematic process capture and AI tractability assessment. Use when documenting workflows, creating SOPs, conducting process discovery interviews, or analyzing automation opportunities. Grounds the SOP-first doctrine in tacit knowledge documentation and structured analysis.

Analyze complex systems, feedback loops, and leverage points. Avoid linear thinking for complex problems.

Auto-tag FF&E products with categories, colors, materials, and style tags using AI. Use when the user asks to "enrich", "tag", or "categorize" products, or to fill in missing category, material, or style columns in the schedule.

Find visually or functionally similar products from an image, name, or description.

Suggest complementary products that pair well with a given item — side tables for sofas, task lights for desks, etc.

Analyze product reviews across any e-commerce platform. Extract actionable insights from customer feedback including pain points, praise patterns, feature requests, and sentiment trends.

Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.

Calculate a productivity score using actual Agent Monitor metrics — session completion rates, cache efficiency (cache_read vs input), compaction pressure (baseline tokens), turn velocity (turn_count / total_turn_duration_ms), tool success ratio (PreToolUse vs PostToolUse), and the workflow intelligence API's complexity and effectiveness scores.

Analyze field progress photos. Catalog, tag, and compare against planned progress.