ReddRadar
Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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image-generation
AI-powered image generation and editing using Google Gemini, Google Imagen, and OpenAI models.
Generate images from text descriptions, edit existing images, create logos/stickers,
apply style transfers, and produce product mockups.
Use this skill when the user requests:
- Image generation from text descriptions
- Image editing or modifications
- Logos, stickers, or graphic design assets
- Product mockups or visualizations
- Style transfers or artistic effects
- Iterative image refinement
Available models:
- Google Gemini: gemini-2.5-flash-image (Nano Banana), gemini-3-pro-image-preview (Nano Banana Pro)
- Google Imagen: imagen-4.0-generate-001, imagen-4.0-ultra-generate-001, imagen-4.0-fast-generate-001
- OpenAI: gpt-image-1.5 (recommended), gpt-image-1, dall-e-3, dall-e-2
Inspired by: https://github.com/EveryInc/every-marketplace/tree/main/plugins/compounding-engineering/skills/gemini-imagegen
jkitchin/skillz 23
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elevenlabs
AI-powered audio generation using ElevenLabs API - text-to-speech with lifelike voices,
sound effects generation, and music creation from text descriptions. Generate natural-sounding
speech in 32 languages, create custom sound effects for games and videos, and compose
royalty-free music tracks.
Use this skill when the user requests:
- Voice generation or text-to-speech conversion
- Audio narration for content (videos, audiobooks, podcasts)
- Sound effects for games, videos, or applications
- Music generation from text descriptions
- Multi-speaker dialogue or conversation audio
- Voice cloning or custom voice creation
- Audio streaming for real-time applications
Capabilities: Text-to-speech (32 languages, 100+ voices), sound effects generation,
music composition, voice cloning, real-time audio streaming
Python SDK: elevenlabs (pip install elevenlabs)
jkitchin/skillz 23
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python-ase
Expert assistance with the Atomic Simulation Environment (ASE) Python library for atomistic simulations, including structure building, calculator setup, optimization, dynamics, and analysis
jkitchin/skillz 23
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python-best-practices
Expert guidance for writing professional Python code following industry best practices
including PEP 8 compliance, testing, type hints, error handling, and modern tooling.
Use this skill when writing new Python code, refactoring existing code, setting up
Python projects, implementing tests, or ensuring code quality and maintainability.
Emphasizes: PEP 8, modularity, DRY principle, TDD, virtual environments (uv),
and modern tooling (Ruff, Black, Mypy).
jkitchin/skillz 23
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materials-properties
Expert assistant for calculating materials properties from first-principles using ASE - structure relaxation, surface energies, adsorption, reaction barriers, phonons, elastic constants, and thermodynamic modeling with proper scientific methodology
jkitchin/skillz 23
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vasp
Expert assistant for VASP (Vienna Ab initio Simulation Package) calculations - input file generation, parameter selection, workflow setup, and best practices for accurate DFT calculations
jkitchin/skillz 23
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python-jax
Expert guidance for JAX (Just After eXecution) - high-performance numerical computing with automatic differentiation, JIT compilation, vectorization, and GPU/TPU acceleration; includes transformations (grad, jit, vmap, pmap), sharp bits, gotchas, and differences from NumPy
jkitchin/skillz 23
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idaes
Comprehensive guidance for using IDAES (Institute for the Design of Advanced Energy Systems)
for process systems engineering. Covers flowsheet modeling, property packages, unit models,
optimization, scaling, initialization, and diagnostics. Use when working with chemical process
simulations, energy systems modeling, power plant design, material and energy balances, or
process optimization. Triggers include 'IDAES', 'flowsheet', 'process model', 'unit operation',
'process optimization', 'property package', 'energy systems', or process engineering tasks.
jkitchin/skillz 23
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pycalphad
Expert guidance for pycalphad - computational thermodynamics library implementing the CALPHAD method for calculating phase diagrams, phase equilibria, and thermodynamic properties of multicomponent materials systems using thermodynamic databases (TDB files)
jkitchin/skillz 23
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python-optimization
Expert guidance for mathematical optimization in Python - systematic problem classification, library selection (scipy, pyomo, cvxpy, GEKKO), solver configuration, and implementation patterns for LP, QP, NLP, MIP, convex, and global optimization problems
jkitchin/skillz 23
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fairchem
Expert guidance for Meta's FAIRChem library - machine learning methods for materials science and quantum chemistry using pretrained UMA models with ASE integration for fast, accurate predictions
jkitchin/skillz 23
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pymatgen
Comprehensive guidance for using pymatgen (Python Materials Genomics) for computational
materials science. Covers structure creation and manipulation, file I/O (CIF, POSCAR, XYZ),
symmetry analysis, Materials Project API integration, phase diagrams, electronic structure
analysis, and DFT input generation. Use when working with crystal structures, materials
properties, computational chemistry calculations, or materials databases. Triggers include
'pymatgen', 'crystal structure', 'Materials Project', 'CIF file', 'POSCAR', 'band structure',
'phase diagram', or materials analysis tasks.
jkitchin/skillz 23
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python-plotting
Comprehensive plotting and visualization in Python - matplotlib (static publication-quality plots), seaborn (statistical visualization), and plotly (interactive plots); includes plot types, customization, best practices, and library selection guidance
jkitchin/skillz 23
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emacs-lisp
Expert guidance for writing professional Emacs Lisp code following the
community-driven Emacs Lisp Style Guide by Bozhidar Batsov. Covers layout,
naming conventions, syntax preferences, macros, documentation, and best practices.
Use this skill when writing Emacs configuration, creating Emacs packages,
writing interactive commands, developing major/minor modes, or refactoring
Emacs Lisp code.
Emphasizes: lexical binding, proper naming, documentation standards, autoloading,
and community conventions.
jkitchin/skillz 23
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python-multiobjective-optimization
Expert guidance for multiobjective optimization in Python - Pareto optimality, evolutionary algorithms (NSGA-II, NSGA-III, MOEA/D), scalarization methods, Pareto front analysis, and implementation with pymoo, platypus, and DEAP
jkitchin/skillz 23
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claude-light
Expert assistant for conducting remote experiments with Claude-Light - a web-accessible RGB LED and spectral sensor instrument for statistics, regression, optimization, and design of experiments
jkitchin/skillz 23
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python-regression-statistics
Expert guidance for regression analysis, statistical modeling, and outlier detection in Python using statsmodels, scikit-learn, scipy, and PyOD - includes model diagnostics, assumption checking, robust methods, and comprehensive outlier detection strategies
jkitchin/skillz 23
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design-of-experiments
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
jkitchin/skillz 23
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phd-qualifier
Expert evaluation of Chemical Engineering PhD qualifying exams - review written reports, presentations, and prepare comprehensive questioning sessions to assess student readiness for doctoral research
jkitchin/skillz 23
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opentrons-gripper
Opentrons Flex Gripper - automated labware movement between deck locations, modules, waste chute, and off-deck storage with precise positioning and offset control for hands-free plate transfers
jkitchin/skillz 23
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opentrons-thermocycler
Opentrons Thermocycler Module - automated PCR thermal cycling with independent block (4-99°C) and lid (37-110°C) temperature control, profile execution, and auto-sealing lid support (GEN2) for high-throughput molecular biology workflows
jkitchin/skillz 23
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opentrons
Expert guidance for Opentrons Python API v2 - automated liquid handling, protocol development, labware management, and hardware module integration for OT-2 and Flex robots
jkitchin/skillz 23
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opentrons-temperature-module
Opentrons Temperature Module - precise heating and cooling (4-95°C) for sample storage, enzyme reactions, and temperature-sensitive protocols with aluminum block adapters for plates, tubes, and PCR strips
jkitchin/skillz 23
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opentrons-magnetic-block
Opentrons Magnetic Block for Flex - unpowered magnetic bead separation using gripper-based labware movement with high-strength neodymium magnets for DNA/RNA purification, immunoprecipitation, and bead-based workflows
jkitchin/skillz 23