量纲分析 是做什么的？
为代码库添加量纲分析注释，记录单位、维度和十进制缩放。当有人要求为代码库注释单位、执行量纲分析，或在DeFi协议、链下代码或其他涉及算术运算的区块链相关代码库中寻找漏洞时使用。防止量纲不匹配，及早捕获公式错误。
为代码库添加量纲分析注释，记录单位、维度和十进制缩放。适用于分析DeFi协议、链下代码或其他涉及算术运算的区块链相关代码中的漏洞，防止量纲不匹配并及早发现公式错误。
该技能旨在通过自动添加量纲分析注释来增强代码库的可读性和安全性，特别适用于DeFi协议、链下代码以及其他涉及复杂算术运算的区块链项目。其主要用途是帮助开发者在代码中明确标注变量和函数的单位、维度和小数缩放比例，从而在早期阶段捕获因单位不匹配或公式错误导致的潜在漏洞。该技能支持多种AI编程助手（如Claude Code、Cursor、Codex等），通过解析代码中的算术运算和数值逻辑，自动生成符合物理或金融量纲规则的注释。例如，它可以识别出价格、数量、利率等变量并标注其单位（如USD、ETH、wei），同时检查运算过程中是否存在维度不一致的问题。使用该技能时，用户只需请求对特定代码库进行量纲分析，AI便会遍历相关代码文件，为关键函数和变量插入注释，并可能标记出潜在的维度错误。这有助于团队维护代码质量，特别是在处理高价值资产和复杂金融逻辑的区块链应用中。
npx skills add https://github.com/trailofbits/skills/tree/main/skills/dimensional-analysisInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
为代码库添加量纲分析注释，记录单位、维度和十进制缩放。当有人要求为代码库注释单位、执行量纲分析，或在DeFi协议、链下代码或其他涉及算术运算的区块链相关代码库中寻找漏洞时使用。防止量纲不匹配，及早捕获公式错误。
This repo contains 20 individual skills — each has its own dedicated page.
AddressSanitizer detects memory errors during fuzzing. Use when fuzzing C/C++ code to find buffer overflows and use-after-free bugs.
AFL++ is a fork of AFL with better fuzzing performance and advanced features. Use for multi-core fuzzing of C/C++ projects.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues. Use when auditing Algorand projects (TEAL/PyTeal).
Clarify requirements before implementing. Use when serious doubts arise.
Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.
Augments Trailmark code graphs with external audit findings from SARIF static analysis results and weAudit annotation files. Maps findings to graph nodes by file and line overlap, creates severity-based subgraphs, and enables cross-referencing findings with pre-analysis data (blast radius, taint, etc.). Use when projecting SARIF results onto a code graph, overlaying weAudit annotations, cross-referencing Semgrep or CodeQL findings with call graph data, or visualizing audit findings in the context of code structure.
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
Prepares codebases for security review using Trail of Bits' checklist. Helps set review goals, runs static analysis tools, increases test coverage, removes dead code, ensures accessibility, and generates documentation (flowcharts, user stories, inline comments).
Searches and explores Burp Suite project files (.burp) from the command line. Use when searching response headers or bodies with regex patterns, extracting security audit findings, dumping proxy history or site map data, or analyzing HTTP traffic captured in a Burp project.
Scans Cairo/StarkNet smart contracts for 6 critical vulnerabilities including felt252 arithmetic overflow, L1-L2 messaging issues, address conversion problems, and signature replay. Use when auditing StarkNet projects.
cargo-fuzz is the de facto fuzzing tool for Rust projects using Cargo. Use for fuzzing Rust code with libFuzzer backend.
Diagnose and fix Claude in Chrome MCP extension connectivity issues. Use when mcp__claude-in-chrome__* tools fail, return "Browser extension is not connected", or behave erratically.
Diagnose and fix Claude in Chrome MCP extension connectivity issues. Use when mcp__claude-in-chrome__* tools fail, return "Browser extension is not connected", or behave erratically.
Runs an autonomous review-and-fix improvement loop over any code target — a skill, plugin, module, or directory — using a reviewer the user names: any installed skill or agent. Keeps a cross-round findings ledger, escalates when fixes stop converging, and guards scope mechanically. Use when asked to 'improve this code until review passes', 'run an improvement loop with <reviewer>', or to iterate review-and-fix with a specific reviewer. For skills prefer the skill-improver entry; for a branch prefer pr-improver.
Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risks, low-level code, and testing. Produces professional scorecard with evidence-based ratings and actionable recommendations.
Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis. Triggers on "run codeql", "codeql scan", "codeql analysis", "build codeql database", or "find vulnerabilities with codeql". Supports "run all" (security-and-quality + security-experimental suites) and "important only" (high-precision security findings) scan modes. Also handles creating data extension models and processing CodeQL SARIF output.
Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.
Constant-time testing detects timing side channels in cryptographic code. Use when auditing crypto implementations for timing vulnerabilities.
Scans Cosmos SDK blockchain modules and CosmWasm contracts for consensus-critical vulnerabilities — chain halts, fund loss, state divergence. 25 core + 16 IBC + 10 EVM + 3 CosmWasm patterns. Use when auditing custom x/ modules, reviewing IBC integrations, or assessing pre-launch chain security. Updated for SDK v0.53.x.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.