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benchflow-ai

benchflow-ai

197 Skills published on GitHub.

obspy-datacenter-client

ObsPy allows you to easily download earthquake data from various data centers/networks through its client API. This is an overview of available services and a demo of the client API for International Federation of Digital Seismograph Networks (FDSN). Use this if you need to download earthquake research data.

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discover-important-function

When given a project codebase, this skill observes the important functions in the codebase for future action.

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fuzzing-python

Creating fuzz driver for Python libraries using LibFuzzer. This skill is useful when agent needs to work with creating fuzz drivers / fuzz targets for Python project and libraries.

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setup-env

When given a Python project codebase, this skill helps the agent to set up virtual environments, install dependencies, and run scripts.

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nlp-research-repo-package-installment

Align Python version and repo-declared dependencies (requirements.txt / environment.yml) before installing packages for NLP research code reproduction.

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cvss-score-extraction

Extract CVSS (Common Vulnerability Scoring System) scores from vulnerability data sources with proper fallback handling. This skill covers understanding CVSS v3, handling multiple score sources (NVD, GHSA, RedHat), implementing source priority logic, and dealing with missing scores in security reporting.

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trivy-offline-vulnerability-scanning

Use Trivy vulnerability scanner in offline mode to discover security vulnerabilities in dependency files. This skill covers setting up offline scanning, executing Trivy against package lock files, and generating JSON vulnerability reports without requiring internet access.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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pcap-triage-tshark

Fast workflow to inspect PCAPs and extract protocol-level details using tshark

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suricata-offline-evejson

Running Suricata against PCAPs offline and validating results via eve.json

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suricata-rules-basics

Core building blocks of Suricata signatures and multi-condition DPI logic

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syz-extract-constants

Defining and extracting kernel constants for syzkaller syzlang descriptions

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syzkaller-build-loop

Full build workflow for adding new syscall descriptions to syzkaller

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syzlang-ioctl-basics

Syzkaller syzlang syntax basics for describing ioctl syscalls

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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.

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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.

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threejs

Three.js scene-graph parsing and export workflows: mesh baking, InstancedMesh expansion, part partitioning, per-link OBJ export, and URDF articulation.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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feature_engineering

Engineer dataset features before ML or Causal Inference. Methods include encoding categorical variables, scaling numerics, creating interactions, and selecting relevant features.

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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.

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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.

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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.

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whisper-transcription

Transcribe audio/video to text with word-level timestamps using OpenAI Whisper. Use when you need speech-to-text with accurate timing information for each word.

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speech-to-text

Transcribe video to timestamped text using Whisper tiny model (pre-installed).

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audio-extractor

Extract audio from video files to WAV format. Use when you need to analyze audio from video, prepare audio for energy calculation, or convert video audio to standard format for processing.

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energy-calculator

Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.

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pause-detector

Detect pauses and silence in audio using local dynamic thresholds. Use when you need to find natural pauses in lectures, board-writing silences, or breaks between sections. Uses local context comparison to avoid false positives from volume variation.

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report-generator

Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.

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segment-combiner

Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.

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silence-detector

Detect initial silence segments in audio/video using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence).

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video-processor

Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses/openings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.

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