「hf」の検索結果

Define custom distance/similarity metrics for clustering and ML algorithms. Use when working with DBSCAN, sklearn, or scipy distance functions with application-specific metrics.

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Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

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Analyze failed GitHub Action jobs for a pull request.

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Basic usage of the General Lake Model (GLM) for lake temperature simulation. Use when you need to run GLM, understand input files, or modify configuration parameters.

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Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.

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Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.

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Use when configuring Maven plugins, setting up common plugins like compiler, surefire, jar, or creating custom plugin executions.

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Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.

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World-class Java and Spring Boot development skill for enterprise applications, microservices, and cloud-native systems. Expertise in Spring Framework, Spring Boot 3.x, Spring Cloud, JPA/Hibernate, and reactive programming with WebFlux. Includes project scaffolding, dependency management, security implementation, and performance optimization.

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Use when erlang distributed systems including node connectivity, distributed processes, global name registration, distributed supervision, network partitions, and building fault-tolerant multi-node applications on the BEAM VM.

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Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.

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Use when oTP behaviors including gen_server for stateful processes, gen_statem for state machines, supervisors for fault tolerance, gen_event for event handling, and building robust, production-ready Erlang applications with proven patterns.

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Comprehensive security engineering skill for application security, penetration testing, security architecture, and compliance auditing. Includes security assessment tools, threat modeling, crypto implementation, and security automation. Use when designing security architecture, conducting penetration tests, implementing cryptography, or performing security audits.

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World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and modern data stack. Includes data modeling, pipeline orchestration, data quality, streaming quality monitoring, and DataOps. Use when designing data architectures, building batch or streaming data pipelines, optimizing data workflows, or implementing data governance.

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**IMPORTANT**: Any change to React or Next.js code must read through this skill first. React and Next.js guidelines from Vercel Engineering covering visual instability, layout shifts, CLS, flickering, hydration issues, and font loading.

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Calibrate GLM parameters for water temperature simulation. Use when you need to adjust model parameters to minimize RMSE between simulated and observed temperatures.

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Detect flood events by comparing water levels to thresholds. Use when determining if flooding occurred, counting flood days, aggregating instantaneous data to daily values, or classifying flood severity.

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Data conditioning techniques for gravitational wave detector data. Use when preprocessing raw detector strain data before matched filtering, including high-pass filtering, resampling, removing filter wraparound artifacts, and estimating power spectral density (PSD). Works with PyCBC TimeSeries data.

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A toolkit for fuzzy string matching and data reconciliation. Useful for matching entity names (companies, people) across different datasets where spelling variations, typos, or formatting differences exist.

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Analyze images and multi-frame sequences using OpenAI GPT vision models

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High-performance numerical computing and machine learning workflows using JAX. Supports array operations, automatic differentiation, JIT compilation, RNN-style scans, map/reduce operations, and gradient computations. Ideal for scientific computing, ML models, and dynamic array transformations.

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Comprehensive clinical laboratory data harmonization for multi-source healthcare analytics. Convert between US conventional and SI units, standardize numeric formats, and clean data quality issues. This skill should be used when you need to harmonize lab values from different sources, convert units for clinical analysis, fix formatting inconsistencies (scientific notation, decimal separators, whitespace), or prepare lab panels for research.

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Calculate the relative contribution of different factors to a response variable using R² decomposition. Use when you need to quantify how much each factor explains the variance of an outcome.

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Detect long-term trends in time series data using parametric and non-parametric methods. Use when determining if a variable shows statistically significant increase or decrease over time.

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。