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Provides a reference for reviewing DeFi smart contracts, programs that manage blockchain transactions. It organizes vulnerability types with causes, code examples, search patterns, and fixes to help investigate accounting, permissions, boundary conditions, and pricing logic.

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• Checking for accounting inconsistencies and missing permission checks
• Comparing normal and alternative code paths
• Reviewing deadline and array boundary conditions

Audit Solidity contracts in Foundry projects before deployment using code analysis, randomized tests, manual review, and private key checks. Produces a JSON report with findings, remediation, test coverage, and a pass or fail deployment decision.

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• Auditing Solidity contracts before deployment
• Adding fuzz and invariant tests for contracts that move funds
• Reviewing private key storage and deployment scripts

Navigate a smart contract security knowledge base in a suggested reading order. Find guides covering audit preparation, vulnerability patterns, code searches, reproduction tests, reporting, case studies, and AI tools without losing track of the next topic.

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• Finding a starting point for learning smart contract auditing
• Following guides from preparation through reporting
• Locating audit case studies

Check mathematical expressions, solve equations, and search bounded ranges for counterexamples using symbolic and numerical libraries. Record assumptions, commands, and results so calculations can be repeated, while keeping computational evidence distinct from general mathematical proof.

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• Checking identities and integrals with exact arithmetic
• Searching a defined range for counterexamples
• Cross-checking numerical results at higher precision

Turn mathematical claims into definitions, lemmas, and proofs for Lean 4 and Mathlib. Check proofs with Lean’s trusted core, separately review whether the formal statement matches the original claim, and record verification evidence.

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• Verifying an important lemma with Lean 4
• Breaking a theorem into definitions and supporting lemmas
• Checking proofs for sorry, admit, and unauthorized axioms

Connect Solidity security analyzers to Claude Code through MCP, a tool connection interface. Combine findings into a report sorted by severity, review contract changes, and generate tests for conditions that should always hold.

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• Combining findings from multiple Solidity analyzers
• Reviewing security issues in contract upgrades
• Generating Foundry invariant tests

Assess Web3 vulnerability findings before submission by checking scope, reproducibility, prerequisites, and attack costs. Organize the root cause, measurable impact, working proof of concept, and proposed fix into an Immunefi report, with examples for comparison.

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• Checking whether a finding is ready for submission
• Drafting an Immunefi vulnerability report
• Reviewing reproduction code and measurable impact

Examine a DeFi yield aggregator, a protocol that collects investment returns, for missing role assignments and failures caused by tiny rewards. Includes a ten-category review, reproducible test templates, and vulnerability report drafts.

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• Checking reward contracts for missing role assignments
• Investigating harvest failures caused by tiny rewards
• Preparing vulnerability reproduction tests and reports

Build runnable Foundry tests that demonstrate smart contract vulnerabilities with before-and-after logs and assertions. Use fork tests, which copy blockchain state, and test helpers to reproduce known DeFi incidents or prepare evidence for a report.

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• Writing runnable proofs of concept for vulnerability reports
• Reproducing issues from a fixed blockchain block
• Controlling callers, time, and balances in tests

Prepare a Web3 bug bounty investigation by scoring targets, setting up analysis tools, reviewing past audits, and tracing how funds move. Use the findings to prioritize smart contracts and assess whether suspected issues have concrete impacts.

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• Choose a protocol for a bug bounty investigation
• Prepare build, test, and static analysis tools
• Map fund flows and prioritize contract reviews

Clarify the next step in a mathematical research task by identifying what is blocking progress. Select one specialist skill for discovery, derivation, computation, proof, or formal verification, with required inputs and clear stopping conditions.

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• Decide where to start with an open mathematical question
• Find the next step when papers, formulas, and code are mixed
• Choose between derivation, computation, proof, and formalization

Turn scattered formulas and theory notes into a derivation that can be checked step by step. Keep definitions and assumptions consistent, distinguish exact identities from approximations, and make hidden conditions and limits explicit.

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• Organize scattered formulas and theory notes
• Trace the steps behind an algebraic identity
• State conditions and error orders for approximations

Analyze Solidity smart contracts with Slither and Mythril before Ethereum deployment. Combine code inspection with execution path analysis, review potential vulnerabilities, remove duplicate findings, and produce an audit report with severity ratings and suggested fixes.

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• Checking Solidity contracts before deployment
• Investigating reentrancy and access control weaknesses
• Consolidating findings from Slither and Mythril

Helps write and review mathematical proofs in natural language. It clarifies assumptions, maps dependencies between claims and lemmas, checks counterexamples and edge cases, and produces a traceable draft that identifies unresolved gaps or necessary changes to the statement.

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• Filling gaps in a mathematical proof draft
• Mapping dependencies between claims and lemmas
• Searching for counterexamples and edge cases

Plan smart contract audits using research from security organizations. Combine threat modeling, static code analysis, fuzzing that varies test inputs, and manual review, while using attack patterns and a four-phase roadmap to guide further learning.

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• Planning a smart contract security audit
• Setting up Echidna or Medusa fuzzing
• Reviewing attack patterns and past audit findings

Choose and configure AI tools for Web3 security work across web applications, APIs, and Solidity contracts. Follow setup examples for reconnaissance, vulnerability validation, and proof-of-concept generation, then combine automated findings with manual review.

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• Choosing AI tools for a security testing target
• Automating web application and API reconnaissance
• Preparing Solidity checks and proof-of-concept code

Uses a completed ZKsync Era investigation with no reportable findings as a defense study. It explains 25 tested attack vectors, the safeguards that blocked them, and criteria for deciding whether to continue reviewing a large bridge protocol.

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• Learning defensive design from a completed ZKsync Era investigation
• Reviewing why 25 tested attack vectors failed
• Assessing whether to continue investigating a large bridge

Shape broad mathematical interests into precise research questions. Search prior work on definitions and theorems, record traceable sources, map supporting and conflicting evidence, and identify gaps that could lead to testable conjectures.

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• Tracing a theorem’s variants and related work
• Checking prior work on an integer sequence
• Defining search terms and the scope of a research question

Use grep text searches to locate Solidity code that needs security review. Ten search groups, priority tiers, and protocol-specific patterns help organize findings and choose where to begin a deeper smart contract audit.

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• Mapping review targets before a smart contract audit
• Searching for a specific vulnerability class
• Prioritizing suspicious code for deeper review

Build reusable Claude Skills from documentation, APIs, code, and specifications. Organize instructions and reference files, define clear activation conditions, add reproducible examples, and check new or existing skills against a delivery checklist.

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• Creating a skill from documentation, code, or specifications
• Reorganizing an overly long SKILL.md
• Clarifying when a skill should activate

Automate tmux, a tool for managing multiple terminal workspaces, to inspect output, send commands, monitor stalled tasks, and record logs. Coordinate multiple AI terminals with task queues, file locks, status tracking, and handoff reports.

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• Inspect output and errors across multiple AI terminals
• Resume tasks waiting for confirmation
• Coordinate tasks and file locks across AI workers