14,446 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Use this skill when the user asks about Clean Architecture in Python — not generic theory, but the specific layer conventions (l1entities, l2usecases, l3interfaceadapters, l4frameworksanddrivers), folder patterns, boundary interfaces, and .importlinter.ini contracts from CJHwong/py-clean-architecture-examples. Fetches…
Write TypeScript code using the Thinkwell framework. Covers the @JSONSchema syntax, Plan fluent API, agent lifecycle, tools, skills, thought streams, and the thinkwell CLI.
Generate NuClaw-compliant Rust code. Use when: create a new module, add a new provider, implement a channel handler, write database operations, add configuration, write tests. Triggers: write rust code for nuclaw, implement this feature in nuclaw, add a new channel/provider, generate tests for nuclaw module. Output…
You are Solidity Smart Contract Engineer, a battle-hardened smart contract developer who lives and breathes the EVM. You treat every wei of gas as precious, every external call as a potential a...
Samurai scoped testing framework for Go (github.com/zerosixty/samurai). MUST use when writing, modifying, reviewing, or debugging Go tests that import samurai, or reference samurai.Run, samurai.RunWith, samurai.Scope, samurai.TestScope, samurai.W, or samurai.BaseContext.
A command-line tool for managing iKuai routers through their local HTTP API. It covers monitoring, network settings, users, security rules, and system administration, with output suited to scripts and AI agents.
Messaging and middleware patterns for Java — in-process events, Spring Events, RabbitMQ, JMS, Kafka, Redis Streams. Graduated complexity from simple to enterprise scale.
A Chinese-language skill for iterating on Solution.cpp, the C++ program for an NSLB leaf-spine network load-balancing challenge, to improve its online evaluation score.
Development discipline from plan to green. New behaviour and known-cause fixes go red-green-refactor with the failing test watched red first, pure refactors go green-to-green with no manufactured red, and how-should-I-write-this questions get verified against current sources before answering. Use when the user says…
Write correct, idiomatic THRML code, centered on Ising machines and how they are trained. THRML is Extropic's JAX-based GPU simulator for the block Gibbs sampling programs that run natively on Extropic's probabilistic computing hardware. Use this skill whenever the user mentions THRML, Extropic, probabilistic…
Tool-neutral CLI agent rules for TI MSPM0 development with SysConfig, DriverLib, CCS, Keil/uVision, CMake/GCC/OpenOCD, and supported board references. Use when an agent needs to inspect or modify MSPM0 projects, validate SysConfig output, package examples, or work on NUEDC embedded firmware.
1C:Enterprise development through the AI-EDT MCP server - BSL analysis and editing, metadata and managed forms, query validation, project diagnostics, debugging, infobase updates and unit tests. Use when the project is a 1C:EDT workspace: BSL modules, .mdo metadata, 1C queries, managed forms. Also use when all you…
Build and debug Pydantic AI v2 agents using best practices for dependencies, instructions, tools, capabilities, hooks, and structured output validation. Use when the user wants to: (1) Create a new Pydantic AI agent, (2) Debug or fix an existing agent, (3) Add features like tools, validators, capabilities, hooks, or…
Go development toolkit: 6 specialized subagents (go-structure-reviewer, go-developer, go-bug-reviewer, go-security-reviewer, go-perf-developer, go-test-developer) and a multi-phase optimization pipeline (go-optimize) for end-to-end Go code review and improvement.
A testing and quality-checking toolkit for running an application, finding bugs, and creating automated tests. It supports API tests and browser-based UI tests in Python or Java.
Guide for training PyTorch models using this template's config-driven pipeline. Use this skill whenever the user wants to: train a model, create experiment configs (run.yaml / opt.yaml / best.yaml), run hyperparameter optimization (HPO) with Optuna, extract best parameters from an HPO study, set up a new experiment…
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originalMIT
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