Automatic Speech Recognition (ASR)
Transcribe audio segments to text using Whisper models. Use larger models (small, base, medium, large-v3) for better accuracy, or faster-whisper for optimized performance. Always align transcription timestamps with diarization segments for accurate speaker-labeled subtitles.
Multimodal Fusion for Speaker Diarization
Combine visual features (face detection, lip movement analysis) with audio features to improve speaker diarization accuracy in video files. Use OpenCV for face detection and lip movement tracking, then fuse visual cues with audio-based speaker embeddings. Essential when processing video files with multiple visible speakers or when audio-only diarization needs visual validation.
speaker-clustering
Cluster audio segments by speaker identity for diarization.
Voice Activity Detection (VAD)
Detect speech segments in audio using VAD tools like Silero VAD, SpeechBrain VAD, or WebRTC VAD. Use when preprocessing audio for speaker diarization, filtering silence, or segmenting audio into speech chunks. Choose Silero VAD for short segments, SpeechBrain VAD for general purpose, or WebRTC VAD for lightweight applications.
Speaker Clustering Methods
Choose and implement clustering algorithms for grouping speaker embeddings after VAD and embedding extraction. Compare Hierarchical clustering (auto-tunes speaker count), KMeans (fast, requires known count), and Agglomerative clustering (fixed clusters). Use Hierarchical clustering when speaker count is unknown, KMeans when count is known, and always normalize embeddings before clustering.
hibernate-upgrade
Migrate Hibernate 5 to Hibernate 6 with Spring Boot 3. Use when fixing HQL/JPQL query parsing issues, removing deprecated Criteria API, updating ID generation strategies, or diagnosing N+1 query behavior changes. Covers breaking changes, type mappings, and performance monitoring.
jakarta-namespace
Migrate Java EE javax.* imports to Jakarta EE jakarta.* namespace. Use when upgrading to Spring Boot 3.x, migrating javax.persistence, javax.validation, javax.servlet imports, or fixing compilation errors after Jakarta EE transition. Covers package mappings, batch sed commands, and verification steps.
restclient-migration
Migrate RestTemplate to RestClient in Spring Boot 3.2+. Use when replacing deprecated RestTemplate with modern fluent API, updating HTTP client code, or configuring RestClient beans. Covers GET/POST/DELETE migrations, error handling, and ParameterizedTypeReference usage.
spring-boot-migration
Migrate Spring Boot 2.x to 3.x with Jakarta EE namespace changes.
spring-security-6
Migrate Spring Security 5 to Spring Security 6 configuration. Use when removing WebSecurityConfigurerAdapter, replacing @EnableGlobalMethodSecurity with @EnableMethodSecurity, converting antMatchers to requestMatchers, or updating to lambda DSL configuration style. Covers SecurityFilterChain beans and authentication manager changes.
hierarchical-taxonomy-clustering
Build unified multi-level category taxonomy from hierarchical product category paths from any e-commerce companies using embedding-based recursive clustering with intelligent category naming via weighted word frequency analysis.
data_cleaning
Clean messy tabular datasets with deduplication, missing value imputation, outlier handling, and text processing. Use when dealing with dirty data that has duplicates, nulls, or inconsistent formatting.
did_causal_analysis
Difference-in-Differences causal analysis to identify demographic drivers of behavioral changes with p-value significance testing. Use for event effects, A/B testing, or policy evaluation.
feature_engineering
Engineer dataset features before ML or Causal Inference. Methods include encoding categorical variables, scaling numerics, creating interactions, and selecting relevant features.
time_series_anomaly_detection
Detect anomalies in time series data using Prophet Framework (Meta), which frames the seasonality, trend holiday effect and other needed regressors into its model, to identify unusual surges or slumps in trends. This is a general methodology analyst can use for understanding what changes of their tracking metrics are manifesting anomalies pattern.
speech-to-text
Transcribe video to timestamped text using Whisper tiny model (pre-installed).
artifact-evaluation
Interact with research artifacts running in separate Docker containers via artifact-runner. Execute commands through HTTP API, read files, and verify artifact functionality.
badge-evaluation
Evaluate research artifacts against NDSS badge criteria (Available, Functional, Reproduced) by checking DOI, documentation, exercisability, and reproducibility requirements.
pdf-reading
Extract text, tables, and structured information from PDF documents using pdfplumber, PyPDF2, or pdftotext command-line tools.
python-json-parsing
>
SQL Ecosystem
This skill should be used when working with SQL databases, "SELECT", "INSERT", "UPDATE", "DELETE", "CREATE TABLE", "JOIN", "INDEX", "EXPLAIN", transactions, or database migrations. Provides comprehensive SQL patterns across PostgreSQL, MySQL, and SQLite.
sql-query
Generate and optimize SQL queries for data retrieval and analysis
sql
Sql standards for sql in Database environments. Covers best practices,
ML Model Training
Build and train machine learning models using scikit-learn, PyTorch, and TensorFlow for classification, regression, and clustering tasks
retention-analysis
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
validation-scripts
Data validation and pipeline testing utilities for ML training projects. Validates datasets, model checkpoints, training pipelines, and dependencies. Use when validating training data, checking model outputs, testing ML pipelines, verifying dependencies, debugging training failures, or ensuring data quality before training.
moai-lang-r
R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.
statistical-analysis
Probability, distributions, hypothesis testing, and statistical inference. Use for A/B testing, experimental design, or statistical validation.
Unit Test Writing
This skill should be used when the user asks to "write tests", "add unit tests", "create test cases", "test this function", "add test coverage", or discusses testing strategies and test implementation.
hierarchical-models
Patterns for hierarchical/multilevel Bayesian models including random effects, partial pooling, and centered vs non-centered parameterizations.
Pandas Data Analysis
Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib
Cross-Site Scripting and HTML Injection Testing
This skill should be used when the user asks to "test for XSS vulnerabilities", "perform cross-site scripting attacks", "identify HTML injection flaws", "exploit client-side injection vulnerabilities", "steal cookies via XSS", or "bypass content security policies". It provides comprehensive techniques for detecting, exploiting, and understanding XSS and HTML injection attack vectors in web applications.
input-validation-xss-prevention
Validate and sanitize user input to prevent XSS, injection attacks, and ensure data quality. Use this skill when you need to validate forms, sanitize user input, prevent cross-site scripting, use Zod schemas, or handle any user-generated content. Triggers include "input validation", "validate input", "XSS", "cross-site scripting", "sanitize", "Zod", "injection prevention", "validateRequest", "safeTextSchema", "user input security".
simon-html-tools
Build single-file HTML tools following Simon Willison's patterns - self-contained HTML+JS+CSS applications optimized for LLM generation, no build step, CDN dependencies. Use when creating browser-based tools, utilities, or demos that should be (1) Self-contained in one HTML file, (2) Easy to distribute and host statically, (3) Quick to prototype with LLMs, (4) Client-side only with no server requirements. Ideal for data visualization, API explorers, format converters, debugging tools, and interactive demos.
python-coder
Modern Python 3.12+ development with uv, ruff, pydantic, FastAPI, async patterns, and production-ready practices.
python-packaging
Automatically applies when configuring Python project packaging. Ensures proper pyproject.toml setup, project layout, build configuration, metadata, and distribution best practices.
setup-to-pyproject
Migrate Python projects from setup.py/setup.cfg to pyproject.toml for use with uv. Use when upgrading legacy Python packaging, converting setup.py to modern pyproject.toml format, setting up dependency groups for development/testing, and ensuring `uv run pytest` works correctly.
jq
Extract specific fields from JSON files efficiently using jq instead of reading entire files, saving 80-95% context.
shell-tools
Production-grade shell tools - jq, xargs, parallel, pipelines
deep-learning
PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production
async-python-patterns
Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
asyncio
Python asyncio - Modern concurrent programming with async/await, event loops, tasks, coroutines, primitives, aiohttp, and FastAPI async patterns
python-async-patterns
Comprehensive guide to Python async/await patterns, best practices, and anti-patterns. Covers asyncio fundamentals, coroutines, async context managers, task management, common libraries (aiohttp, aiofiles, asyncpg), framework integration (FastAPI, Django), performance considerations, and proper exception handling. Use when reviewing or writing asynchronous Python code.
python-async
|
chess-commentator
This skill should be used when analyzing chess positions. Automatically triggers when users provide FEN positions for analysis or ask about specific chess positions. Provides engine-powered analysis with natural language explanations of best moves, key variations, and strategic/tactical themes.
python-dev
Python development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).
Designing Before Coding
Design in pseudocode first, iterate approaches, then translate to code
implementation
Implement features with code, tests, and documentation. Use when building features from approved designs following TDD and project coding standards.
python-coding
Best practices for writing high quality production grade Python code
c-incremental-build-converter
Convert C/C++ project build.sh and test.sh scripts to support incremental builds. Use when fixing build scripts for re-execution after docker commit, converting to out-of-tree builds, or making scripts idempotent for repeated execution.
Page 2 of 9 · 440 results