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This skill guides writing DigitalOcean infrastructure with OpenTofu/Terraform. Use when provisioning Droplets, VPCs, Managed Databases, Firewalls, or other DO resources.

Guidance for implementing batching schedulers for LLM inference systems with compilation-based accelerators. This skill applies when optimizing request batching to minimize cost while meeting latency thresholds, particularly when dealing with shape compilation costs, padding overhead, and multi-bucket request distributions. Use this skill for tasks involving batch planning, shape selection, generation-length bucketing, and cost-model-driven optimization for neural network inference.

Guidance for removing JavaScript from HTML while preserving structure and formatting. This skill applies when filtering XSS vectors, sanitizing HTML content, removing script tags and event handlers, or building HTML sanitization tools. It covers comprehensive XSS vector identification, format-preserving transformations, and verification strategies.

This skill guides Backblaze B2 Cloud Storage integration with OpenTofu/Terraform and B2 CLI. Use when managing B2 buckets, application keys, file uploads, lifecycle rules, or S3-compatible storage.

Guidance for extracting text-based game commands, moves, or inputs from video recordings using OCR and frame analysis. This skill applies when extracting user inputs from screen recordings of text-based games (Zork, interactive fiction), terminal sessions, or any video where typed commands need to be recovered. It covers OCR preprocessing, region-of-interest extraction, domain-aware validation, and deduplication strategies.

This skill provides guidance for FEAL cipher linear cryptanalysis tasks. It should be used when recovering encryption keys from FEAL-encrypted data using known plaintext-ciphertext pairs, implementing linear approximation attacks on block ciphers, or solving cryptanalysis challenges involving the FEAL cipher family. The skill emphasizes mathematical analysis over brute-force approaches.

Guidance for setting up legacy Windows VMs (like Windows 3.11) in QEMU with web-based remote access via noVNC. This skill should be used when tasks involve running legacy operating systems in virtual machines, configuring QEMU for older OS images, setting up VNC/noVNC web interfaces, or establishing programmatic keyboard control via QMP. Covers VM boot verification strategies, nginx reverse proxy configuration, and websockify setup.

Guidance for extracting and processing data from ELF (Executable and Linkable Format) binary files. This skill should be used when tasks involve parsing ELF headers, reading program segments, extracting memory contents, or converting binary data to structured formats like JSON. Applicable to reverse engineering, binary analysis, and memory dump extraction tasks.

This skill provides guidance for reverse engineering compiled binaries to produce equivalent source code. It applies when tasks require analyzing executables, extracting algorithms and constants, and recreating identical program behavior in source form. Use when the goal is byte-for-byte or pixel-perfect reproduction of binary output.

Build edge-first TypeScript applications on Cloudflare Workers. Covers Workers API, Hono framework, KV/D1/R2 storage, Durable Objects, Queues, and testing patterns. Use when creating serverless workers, edge functions, or Cloudflare-deployed services.

This skill provides guidance for implementing custom compression encoders that must be compatible with existing decoders (especially arithmetic coding). It should be used when the task requires writing a compressor/encoder that produces output compatible with a given decompressor/decoder, or when implementing arithmetic coding or similar bit-level compression schemes.

This skill provides guidance for tasks involving merging git branches that contain different implementations of ARC-AGI pattern recognition algorithms, and then implementing a working solution that generalizes across examples. Use this skill when the task involves (1) merging git branches with conflicting code, (2) analyzing ARC-AGI style input/output grid transformations, or (3) implementing pattern recognition algorithms that must generalize to unseen test cases.

Guide for configuring Nginx web server with custom request logging, rate limiting, and error pages. This skill should be used when tasks involve Nginx installation, configuration, custom log formats, rate limiting setup, or custom error page creation.

Create scroll-triggered and entrance animations using Framer Motion (motion package). Use when adding animations, implementing scroll reveals, or migrating from CSS/Intersection Observer.

Guides AILANG parser development with conventions and patterns. Use when user wants to modify parser, understand parser architecture, or debug parser issues. Saves 30% of development time by preventing token position bugs.

Guidance for converting R-Stan (RStan) code to Python-Stan (PyStan). This skill applies when translating Stan models and inference code from R to Python, including API mapping between RStan and PyStan 3.x, hyperparameter translation, and handling differences in output formats. Use this skill for statistical model migration, Bayesian inference code conversion, or when working with Stan models across R and Python ecosystems.

Extracts hidden or encoded text from GCODE files by analyzing toolpath geometry and coordinate data. This skill should be used when tasks involve decoding text from 3D printing files, recovering embossed or engraved text from GCODE, or CTF-style challenges involving GCODE analysis. Applies to any task requiring geometric reconstruction of text from CNC or 3D printer movement commands.

Guidance for building and training with the Caffe deep learning framework on CIFAR-10 dataset. This skill applies when tasks involve compiling Caffe from source, training convolutional neural networks on image classification datasets, or working with legacy deep learning frameworks that have compatibility issues with modern systems.

This skill guides provisioning Hetzner Cloud infrastructure with OpenTofu/Terraform. Use when creating servers, networks, firewalls, load balancers, or volumes on Hetzner Cloud.

Guidance for creating standalone CLI tools that perform neural network inference by extracting PyTorch model weights and reimplementing inference in C/C++. This skill applies when tasks involve converting PyTorch models to standalone executables, extracting model weights to portable formats (JSON), implementing neural network forward passes in C/C++, or creating CLI tools that load images and run inference without Python dependencies.