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exoplanet-workflows

General workflows and best practices for exoplanet detection and characterization from light curve data. Use when planning an exoplanet analysis pipeline, understanding when to use different methods, or troubleshooting detection issues.

benchflow-ai
benchflow-ai
1,819369

ffmpeg-keyframe-extraction

Extract key frames (I-frames) from video files using FFmpeg command line tool. Use this skill when the user needs to pull out keyframes, thumbnails, or important frames from MP4, MKV, AVI, or other video formats for analysis, previews, or processing.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

find-bugs

Find bugs, security vulnerabilities, and code quality issues in local branch changes. Use when asked to review changes, find bugs, security review, or audit code on the current branch.

benchflow-ai
benchflow-ai
1,819369

finite-horizon-lqr

Solving finite-horizon LQR via dynamic programming for MPC.

benchflow-ai
benchflow-ai
1,819369

first-order-model-fitting

Fit first-order dynamic models to experimental step response data and extract K (gain) and tau (time constant) parameters.

benchflow-ai
benchflow-ai
1,819369

fjsp-baseline-repair-with-downtime-and-policy

This skill should be considered when you need to repair an infeasible or non-optimal flexible job scheduling planning schedule into a downtime-feasible, precedence-feasible one while keep no worse policy budget.

benchflow-ai
benchflow-ai
1,819369

flood-detection

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.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

fuzzy-match

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.

benchflow-ai
benchflow-ai
1,819369

fuzzy-name-search

This skill includes search capability in 13F, such as fuzzy search a fund information using possibly inaccurate name, or fuzzy search a stock cusip info using its name.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

gemini-count-in-video

Analyze and count objects in videos using Google Gemini API (object counting, pedestrian detection, vehicle tracking, and surveillance video analysis).

benchflow-ai
benchflow-ai
1,819369

gemini-video-understanding

Analyze videos with Google Gemini API (summaries, Q&A, transcription with timestamps + visual context, scene/timeline detection, video clipping, FPS control, multi-video comparison, and YouTube URL analysis).

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

gh-cli

The gh CLI is GitHub's official command line tool for interacting with GitHub repositories, issues, pull requests, and more. When needs to interact with GitHub repositories, issues, pull requests, and more, use this skill.

benchflow-ai
benchflow-ai
1,819369

glm-basics

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.

benchflow-ai
benchflow-ai
1,819369

glm-calibration

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

benchflow-ai
benchflow-ai
1,819369

glm-output

Read and process GLM output files. Use when you need to extract temperature data from NetCDF output, convert depth coordinates, or calculate RMSE against observations.

benchflow-ai
benchflow-ai
1,819369

gmail-skill

Manage Gmail - send, read, search emails, manage labels and drafts. Use when user wants to interact with their Gmail account for email operations.

benchflow-ai
benchflow-ai
1,819369

gpt-multimodal

Analyze images and multi-frame sequences using OpenAI GPT series

benchflow-ai
benchflow-ai
1,819369

gtts

Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.

benchflow-ai
benchflow-ai
1,819369

hex-grid-spatial

Hex grid spatial utilities for offset coordinate systems. Use when working with hexagonal grids, calculating distances, finding neighbors, or spatial queries on hex maps.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

image-ocr

Extract text content from images using Tesseract OCR via Python

benchflow-ai
benchflow-ai
1,819369

imc-tuning-rules

Calculate PI/PID controller gains using Internal Model Control (IMC) tuning rules for first-order systems.

benchflow-ai
benchflow-ai
1,819369

integral-action-design

Adding integral action to MPC for offset-free tension tracking.

benchflow-ai
benchflow-ai
1,819369

jackson-security

Security considerations for Jackson JSON deserialization in Java applications. Covers timing of validation, raw input interception, and common deserialization attack patterns.

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

jax-skills

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.

benchflow-ai
benchflow-ai
1,819369

lab-unit-harmonization

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.

benchflow-ai
benchflow-ai
1,819369

lean4-memories

This skill should be used when working on Lean 4 formalization projects to maintain persistent memory of successful proof patterns, failed approaches, project conventions, and user preferences across sessions using MCP memory server integration

benchflow-ai
benchflow-ai
1,819369

lean4-theorem-proving

Use when working with Lean 4 (.lean files), writing mathematical proofs, seeing "failed to synthesize instance" errors, managing sorry/axiom elimination, or searching mathlib for lemmas - provides build-first workflow, haveI/letI patterns, compiler-guided repair, and LSP integration

benchflow-ai
benchflow-ai
1,819369

light-curve-preprocessing

Preprocessing and cleaning techniques for astronomical light curves. Use when preparing light curve data for period analysis, including outlier removal, trend removal, flattening, and handling data quality flags. Works with lightkurve and general time series data.

benchflow-ai
benchflow-ai
1,819369

locational-marginal-prices

Extract locational marginal prices (LMPs) from DC-OPF solutions using dual values. Use when computing nodal electricity prices, reserve clearing prices, or performing price impact analysis.

benchflow-ai
benchflow-ai
1,819369

lomb-scargle-periodogram

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.

benchflow-ai
benchflow-ai
1,819369

manufacturing-failure-reason-codebook-normalization

This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

benchflow-ai
benchflow-ai
1,819369

map-optimization-strategy

Strategy for solving constraint optimization problems on spatial maps. Use when you need to place items on a grid/map to maximize some objective while satisfying constraints.

benchflow-ai
benchflow-ai
1,819369

marker

Convert PDF documents to Markdown using marker_single. Use when Claude needs to extract text content from PDFs while preserving LaTeX formulas, equations, and document structure. Ideal for academic papers and technical documents containing mathematical notation.

benchflow-ai
benchflow-ai
1,819369

matched-filtering

Matched filtering techniques for gravitational wave detection. Use when searching for signals in detector data using template waveforms, including both time-domain and frequency-domain approaches. Works with PyCBC for generating templates and performing matched filtering.

benchflow-ai
benchflow-ai
1,819369

maven-build-lifecycle

Use when working with Maven build phases, goals, profiles, or customizing the build process for Java projects.

benchflow-ai
benchflow-ai
1,819369

maven-dependency-management

Use when managing Maven dependencies, resolving dependency conflicts, configuring BOMs, or optimizing dependency trees in Java projects.

benchflow-ai
benchflow-ai
1,819369

maven-plugin-configuration

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

benchflow-ai
benchflow-ai
1,819369

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.

benchflow-ai
benchflow-ai
1,819369

mesh-analysis

Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.

benchflow-ai
benchflow-ai
1,819369

meteorology-driver-classification

Classify environmental and meteorological variables into driver categories for attribution analysis. Use when you need to group multiple variables into meaningful factor categories.

benchflow-ai
benchflow-ai
1,819369

mhc-algorithm

Implement mHC (Manifold-Constrained Hyper-Connections) for stabilizing deep network training. Use when implementing residual connection improvements with doubly stochastic matrices via Sinkhorn-Knopp algorithm. Based on DeepSeek's 2025 paper (arXiv:2512.24880).

benchflow-ai
benchflow-ai
1,819369

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Adoption

Agent Skills are supported by leading AI development tools.

FAQ

Frequently asked questions about Agent Skills.

01

What are Agent Skills?

Agent Skills are reusable, production-ready capability packs for AI agents. Each skill lives in its own folder and is described by a SKILL.md file with metadata and instructions.

02

What does this agent-skills.md site do?

Agent Skills is a curated directory that indexes skill repositories and lets you browse, preview, and download skills in a consistent format.

03

Where are skills stored in a repo?

By default, the site scans the skills/ folder. You can also submit a URL that points directly to a specific skills folder.

04

What is required inside SKILL.md?

SKILL.md must include YAML frontmatter with at least name and description. The body contains the actual guidance and steps for the agent.

05

How can I submit a repo?

Click Submit in the header and paste a GitHub URL that points to a skills folder. We’ll parse it and add any valid skills to the directory.