TTS Audio Mastering
Practical mastering steps for TTS audio: cleanup, loudness normalization, alignment, and delivery specs.
docx
Word document manipulation with python-docx - handling split placeholders, headers/footers, nested tables
file-organizer
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
planning-with-files
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
academic-pdf-redaction
Redact text from PDF documents for blind review anonymization
memory-optimization
Optimize Python code for reduced memory usage and improved memory efficiency. Use when asked to reduce memory footprint, fix memory leaks, optimize data structures for memory, handle large datasets efficiently, or diagnose memory issues. Covers object sizing, generator patterns, efficient data structures, and memory profiling strategies.
python-parallelization
Transform sequential Python code into parallel/concurrent implementations. Use when asked to parallelize Python code, improve code performance through concurrency, convert loops to parallel execution, or identify parallelization opportunities. Handles CPU-bound (multiprocessing), I/O-bound (asyncio, threading), and data-parallel (vectorization) scenarios.
vulnerability-csv-reporting
Generate structured CSV security audit reports from vulnerability data with proper filtering and formatting. This skill covers CSV schema design for security reports, using Python csv.DictWriter, severity-based filtering, and field mapping from JSON to tabular format.
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 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.
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.
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 applications to Spring Boot 3.x. Use when updating pom.xml versions, removing deprecated JAXB dependencies, upgrading Java to 17/21, or using OpenRewrite for automated migration. Covers dependency updates, version changes, and migration checklist.
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.
pcap-triage-tshark
Fast workflow to inspect PCAPs and extract protocol-level details using tshark
suricata-offline-evejson
Running Suricata against PCAPs offline and validating results via eve.json
suricata-rules-basics
Core building blocks of Suricata signatures and multi-condition DPI logic
syz-extract-constants
Defining and extracting kernel constants for syzkaller syzlang descriptions
syzkaller-build-loop
Full build workflow for adding new syscall descriptions to syzkaller
syzlang-ioctl-basics
Syzkaller syzlang syntax basics for describing ioctl syscalls
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.
obj-exporter
Three.js OBJExporter utility for exporting 3D geometry to Wavefront OBJ format. Use when converting Three.js scenes, meshes, or geometries to OBJ files for use in other 3D software like Blender, Maya, or MeshLab.
threejs
Three.js scene-graph parsing and export workflows: mesh baking, InstancedMesh expansion, part partitioning, per-link OBJ export, and URDF articulation.
search-accommodations
Lookup accommodations by city from the bundled dataset. Use this skill when you need to recommend places to stay in a given city or filter lodging options before building an itinerary.
search-attractions
Retrieve attractions by city from the bundled dataset. Use this skill when surfacing points of interest or building sightseeing suggestions for a destination.
search-cities
List cities for a given state using the bundled background data. Use this skill to validate state inputs or expand destination choices before flight/restaurant/attraction/driving/accommodation lookups.
search-driving-distance
Estimate driving/taxi duration, distance, and rough cost between two cities using the bundled distance matrix CSV. Use this skill when comparing ground travel options or validating itinerary legs.
search-flights
Search flights by origin, destination, and departure date using the bundled flights dataset. Use this skill when proposing flight options or checking whether a route/date combination exists.
search-restaurants
Retrieve restaurants by city from the bundled dataset. Use this skill when recommending places to eat or validating dining options for a destination.
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.
ffmpeg-video-editing
Video editing with ffmpeg including cutting, trimming, concatenating segments, and re-encoding. Use when working with video files (.mp4, .mkv, .avi) for: removing segments, joining clips, extracting portions, or any video manipulation task.
filler-word-processing
Process filler word annotations to generate video edit lists. Use when working with timestamp annotations for removing speech disfluencies (um, uh, like, you know) from audio/video content.
speech-to-text
Transcribe video to timestamped text using Whisper tiny model (pre-installed).
pdf-editing
Complete guide for reading and editing PDF documents with PyMuPDF.
text-parser
Guide for parsing structured text input files.
egomotion-estimation
Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.
output-validation
Local self-check of instructions and mask outputs (format/range/consistency) without using GT.
sampling-and-indexing
Standardize video sampling and frame indexing so interval instructions and mask frames stay aligned with a valid key/index scheme.
gamma-phase-associator
An overview of the python package for running the GaMMA earthquake phase association algorithm. The algorithm expects phase picks data and station data as input and produces (through unsupervised clustering) earthquake events with source information like earthquake location, origin time and magnitude. The skill explains commonly used functions and the expected input/output format.
obspy-data-api
An overview of the core data API of ObsPy, a Python framework for processing seismological data. It is useful for parsing common seismological file formats, or manipulating custom data into standard objects for downstream use cases such as ObsPy's signal processing routines or SeisBench's modeling API.
seisbench-model-api
An overview of the core model API of SeisBench, a Python framework for training and applying machine learning algorithms to seismic data. It is useful for annotating waveforms using pretrained SOTA ML models, for tasks like phase picking, earthquake detection, waveform denoising and depth estimation. For any waveform, you can manipulate it into an obspy stream object and it will work seamlessly with seisbench models.
seismic-picker-selection
This is a summary the advantages and disadvantages of earthquake event detection and phase picking methods, shared by leading seismology researchers at the 2025 Earthquake Catalog Workshop. Use it when you have a seismic phase picking task at hand.
geospatial-analysis
Analyze geospatial data using geopandas with proper coordinate projections. Use when calculating distances between geographic features, performing spatial filtering, or working with plate boundaries and earthquake data.
timeseries-detrending
Tools and techniques for detrending time series data in macroeconomic analysis. Use when working with economic time series that need to be decomposed into trend and cyclical components. Covers HP filter, log transformations for growth series, and correlation analysis of business cycles.
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