Coding standards, frameworks, refactoring, and code review (16.9K skills)
Map common Python modules and idioms to Scala libraries and approaches. Use examples to translate JSON, dates, files, regular expressions, HTTP requests, logging, tests, configuration, command-line arguments, and asynchronous work.
Choose and implement ways to distribute parallel tasks across workers, processes, or nodes. It covers fixed and dynamic partitioning, work stealing, and adaptive scheduling to reduce uneven workloads and slow stragglers.
Tune model predictive control (MPC) for tension control in web handling by choosing a prediction horizon and state and control cost weights. Understand how these choices affect disturbance rejection, tracking, actuator effort, response speed, and computation.
Compare and implement eviction policies for capacity-limited caches, including LRU, LFU, FIFO, S3FIFO, and ARC. Understand how hit handling and admission differ, avoid common implementation mistakes, and evaluate policies by replaying the same workload trace.
Configure Maven plugins for compiling Java, running unit and integration tests, checking code quality, packaging artifacts, and managing versions or releases. It explains plugin versions, shared settings, lifecycle phases, and common configuration pitfalls.
Build Erlang applications across multiple BEAM nodes. Get guidance on node connections, remote messaging and calls, global process names, distributed supervision, and handling network partitions to keep services resilient.
Calculate PI controller gains for a first-order process from its gain and time constant using Internal Model Control (IMC). Choose a response speed setting and get proportional and integral gains for control work.
Plan step tests for identifying an unknown control system. Get practical guidance on test duration, sampling rate, input size, and which input and output measurements to record for estimating system parameters from its response.
Learn how to structure Erlang applications with OTP behaviors: use gen_server for stateful processes, gen_statem for explicit state transitions, gen_event for event handling, and supervisors to restart failed processes.
Manage dependencies in Java projects with Maven by organizing versions and scopes, importing BOMs for shared version control, inspecting dependency trees, and resolving conflicts between direct and transitive dependencies.
Carry project knowledge between Lean 4 proof sessions with an MCP memory server. The skill stores and retrieves successful proof patterns, failed tactics, project conventions, theorem relationships, and user preferences, helping the agent use relevant past experience when working on similar goals.
Configure Maven builds for Java projects by choosing lifecycle phases and goals, defining profiles for different environments, and adjusting tests, resources, and modules. Use it to understand build commands, investigate failures, or tune project build settings.
Review or build web UI components against practical guidance for accessibility, performance, animation, and visual stability. It helps identify issues such as missing labels, unstable image layouts, inaccessible focus states, and inefficient rendering patterns.
Use this guide when building or refactoring React and Next.js applications. Its prioritized rules cover async work, bundle size, server and client data fetching, rerenders, rendering, and JavaScript performance, with examples to help agents improve code.
Reviews failed GitHub Actions job logs for a pull request or specific job URLs. It returns a concise summary of the likely root cause, error messages, test names, and relevant log excerpts, so you can see what needs attention.
Support Java and Spring Boot development with project scaffolding, generated JPA layers and REST endpoints, security configuration, dependency checks, and JVM performance guidance. It includes Python tools and references for enterprise applications, microservices, and reactive services.
Use uv to create Python projects, manage packages and virtual environments, and install Python versions. Learn workflows for lockfiles, existing projects, monorepos, CI, and Docker, with commands for migrating from tools such as pip or Poetry.
Design concurrent Erlang systems using lightweight processes that communicate through messages. The skill explains spawning, request-response patterns, selective receive, links and monitors for detecting failures, timeouts, and supervision approaches for fault handling on the BEAM VM.
Simulate a quadrotor’s physical motion by converting desired thrust and moments into motor speeds, modeling motor lag, and integrating translational and rotational equations of motion with RK45. The skill describes the state values and motor limits used in the simulation.
Compute active and reactive power flows at both ends of an AC power line, accounting for transformer tap ratios and phase shifts. The skill also covers apparent power, bus balance aggregation, MVA limit checks, and branch loading calculations.
Navigate the TRL library codebase with a guide to its SFT, DPO, GRPO, and KTO trainers, shared utilities, configuration, and model wrappers. Use it to understand expected contracts and data flow before inspecting or changing trainer code.
Work with hex maps that use odd-r offset coordinates, where odd rows shift right. The skill explains how to find six neighbors, calculate distance between tiles, check adjacency, and list tiles within a chosen radius.
Use this guide to implement a quadrotor’s inner attitude loop. It explains how to turn desired horizontal acceleration into roll and pitch targets, then use PID feedback to calculate control moments, with guidance on integral state and gain adjustments.
Implement a quadrotor’s outer position-control loop and plan trajectories from takeoff, hover, fly, and land waypoints. It covers PID feedback for desired acceleration and thrust, plus a sampled state matrix with position, velocity, orientation, angular velocity, and acceleration.