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Found 523 Skills
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Deep codebase analysis for building architectural context before vulnerability or bug finding. Uses line-by-line analysis with First Principles, 5 Whys, and 5 Hows. Use when deep comprehension is needed before security auditing, architecture review, or threat modeling.
Verify, check, transform, and repair Lean 4 proofs using the Axiom (Axle) CLI and API. Supports proof verification, syntax checking, theorem extraction, code transformation (rename, merge, simplify), proof repair, and disproving. Use this skill whenever the user works with Lean 4 code, formal mathematics, Mathlib theorems, or mentions axiom, axle, lean verify, proof verification, formal proof, or theorem checking -- even if they don't explicitly say "axiom" but are clearly working with Lean proofs that need machine verification.
Writes Kani bounded model checker proofs for Rust programs. Proves conservation, isolation, arithmetic safety, and access control properties. Use when the user asks to write formal verification, Kani proofs, model checking, or when code contains kani::,
Tauri v2 跨平台应用开发指南。用于开发桌面 (macOS/Windows/Linux) 和移动端 (iOS/Android) 应用。包含项目初始化、Rust 后端、React 前端集成、移动端配置等最佳实践。当需要创建 Tauri 项目、配置移动端支持、编写 Rust 命令、或解决 Tauri 相关问题时使用此 skill。
Code Porter Skill: Prioritize adopting excellent open-source projects, avoid reinventing the wheel unnecessarily. Use when: You need to implement new features, select technical solutions, or evaluate whether to build something from scratch. Triggers: "implement", "develop", "create", "build", "write a", "make a"
Structured Solana smart contract security audit using parallel scanning agents with confidence-scored findings. Use when the user asks to audit, review, or analyze a Solana program for security vulnerabilities, or when code contains solana_program, anchor_lang, pinocchio,
Coverage-guided fuzzing workflow for C/C++, Rust, and Go targets. Runs audit-context-building to find suspicious code, writes a targeted harness, builds with sanitizers, runs the fuzzer, and reports crashes.
Benchmark any agent skill to measure whether it actually improves performance. Use when the user wants to evaluate, test, or compare a skill against baseline, or when they mention "benchmark", "eval", "skill performance", or "does this skill help". Runs isolated eval sessions with and without the skill, grades outputs via layered grading (deterministic checks + LLM-as-judge), analyzes behavioral signals, and generates a comparison report with a USE / DON'T USE verdict.
Local pentest sandbox for a full black-box engagement. Triggers on "kage", "pentest", "security audit on", "audit the security of". Runs recon, deep testing, exploit verification, and judging inside a per-engagement Kali Docker container. Each host working directory gets its own isolated sandbox. Produces `./results/<target>/audit-report.md`.
Check whether a Playwright, Puppeteer, Selenium or CDP-driven browser presents a coherent fingerprint, using liarjs as a library against a Page you already have - navigator.webdriver, HeadlessChrome tokens, worker versus main-thread identity, patched-API integrity, WebGL versus WebGPU GPU identity. Use when asked whether an automated browser looks like a normal one, when a headless setup or a stealth plugin's effect needs measuring rather than assuming, or when an assertion on fingerprint quality belongs in a test suite.
Read a liarjs fingerprint report and attribute each failing check to the component that produced it - what the check id measures, whether the signal comes from the launch configuration, the page-modifying layer, the network path or the machine image, and which failures are inherent to headless or datacenter environments. Use when a fingerprint scan came back with a low score, or when a check id such as webdriver, worker-consistency, gpu-triad, native-integrity or tz needs explaining.