SKILLS/analyzing-ethereum-smart-contract-vulnerabilities/SKILL.md
Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet.
npx skillsauth add pinkpixel-dev/skills-collection-1 analyzing-ethereum-smart-contract-vulnerabilitiesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Smart contract vulnerabilities have led to billions of dollars in losses across DeFi protocols. Unlike traditional software, deployed smart contracts are immutable and handle real financial assets, making pre-deployment security analysis critical. Slither performs fast static analysis using an intermediate representation to detect over 90 vulnerability patterns in seconds, while Mythril uses symbolic execution and SMT solving to discover complex execution path vulnerabilities like reentrancy and integer overflows. This skill covers running both tools against Solidity contracts, interpreting results, triaging findings by severity, and generating audit reports.
Execute Slither against the contract codebase to identify vulnerability patterns, optimization opportunities, and code quality issues using its 90+ built-in detectors.
Run Mythril deep analysis to explore execution paths and discover reentrancy, unchecked external calls, and arithmetic vulnerabilities that require path-sensitive analysis.
Combine results from both tools, deduplicate findings, assess severity based on exploitability and financial impact, and filter false positives.
Produce a structured audit report with vulnerability descriptions, affected code locations, exploit scenarios, and remediation recommendations.
JSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.
testing
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.