浏览和安装 Killer-Skills 目录中的数千个 AI Agent 技能。支持 Claude Code、Windsurf、Cursor 等。
IDA Pro Python scripting for reverse engineering. Use when writing IDAPython scripts, analyzing binaries, working with IDAs API for disassembly, decompilation (Hex-Rays), type systems, cross-references, functions, segments, or any IDA database manipulation. Covers ida_* modules (50+), idautils iterators, and common patterns.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Run repeatable inference smoke tests using geppetto/pinocchio example binaries (single-pass, streaming, tool-loop, OpenAI Responses thinking) including tmux-driven TUI tests. Use when refactors touch InferenceState/Session/EngineBuilder, tool calling loop, event sinks, provider request formatting, or when you need a quick does inference still work? checklist.
This skill should be used when writing unit tests, TDD test cases, test coverage analysis, or test-driven development for NG component Pattern methods (e.g., OnModifyDone, OnDirtyLayoutWrapperSwap). Covers test principles, templates, common pitfalls, branch coverage, API verification, state reset, and mandatory self-checklist for ace_engine testing.
Analyze student git activity, lab submissions, and project work for software engineering courses. Use when asked to update student analysis, check student activity, analyze the class, or when working with student rosters and git repositories. Handles inconsistencies in student behavior like multiple usernames, name variations, and missing data.
Use this skill when building AI features, integrating LLMs, implementing RAG, working with embeddings, deploying ML models, or doing data science. Activates on mentions of OpenAI, Anthropic, Claude, GPT, LLM, RAG, embeddings, vector database, Pinecone, Qdrant, LangChain, LlamaIndex, DSPy, MLflow, fine-tuning, LoRA, QLoRA, model deployment, ML pipeline, feature engineering, or machine learning.
Senior Security Engineer specializing in JWT authentication, Spring Security, OAuth2, RBAC, and secure coding practices for financial applications. Use when implementing authentication flows, configuring security policies, reviewing code for vulnerabilities, setting up CORS, managing JWT keys, or handling user authorization. Expert in RS256, refresh token rotation, password hashing with BCrypt, and secure API design.
Analyze product/feature requirements for the PigeonPod project with software engineering rigor. Use when users ask to evaluate a requirements value, feasibility, architecture fit, implementation impact, risk, delivery scope, or tradeoffs. Always inspect current repository docs/code first (especially architecture and README files), then use MCP tools (including Context7) to verify external library/framework/API constraints before concluding.
This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on binary, executable, ELF, what does this do, reverse engineer, disassemble, decompile, pyc file, python bytecode, analyze binary, figure out, marshal. Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.
Write, critique, and iterate prompts for OpenAI GPT-5 series models. Use for tasks like: (1) turning vague requirements into high-signal instructions, (2) selecting between quick vs deep reasoning behaviors, (3) creating robust structured-output prompts (JSON schemas, tool calls), (4) designing evaluation prompts and rubrics, and (5) debugging prompt failures (hallucinations, format drift, tool misuse). Trigger when the user mentions GPT-5, prompt engineering, system/developer messages, structured outputs, agent prompts, or wants best-practice templates.
Practice radical candor by delivering only verified, tested code with data-backed decisions, immediate problem flagging, and honest status communication. Use this skill when making claims about code behavior, reporting system status, identifying risks, documenting missing coverage, or challenging assumptions. Applies to all development activities requiring factual accuracy, evidence-based assertions, gap ownership, and closing the loop on delivered work through validation and independent review.