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    Advanced Code Reviewer & Bug Fixer

    1

    Advanced code review and debugging agent for identifying logic flaws, security risks, and performance bottlenecks.

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    Advanced Code Reviewer & Bug Fixer

    Advanced Code Reviewer & Bug Fixer

    Example session with this skill installed

    Review this TypeScript function for concurrency issues and provide a fix:

    async function updateBalance(userId: string, amount: number) {
      const user = await db.users.find(userId);
      user.balance += amount;
      await db.users.save(user);
    }
    
    • Read your context and instructions
    • Compiled the advanced code reviewer

    I have analyzed the provided updateBalance function. It contains a critical concurrency defect.

    Finding: Race Condition in Read-Modify-Write Cycle

    AttributeDetail
    SeverityHigh
    ConfidenceHigh
    LocationupdateBalance function
    ImpactData corruption / Lost updates to user balance

    Analysis

    The current implementation fetches the user object, modifies the balance in application memory, and then saves it back. If two requests for the same userId occur simultaneously, they will both read the same initial balance, calculate their respective updates, and the last one to save will overwrite the other, leading to a "lost update" scenario.

    Fix

    Use an atomic database update to ensure the increment happens at the engine level, or implement optimistic locking.

    async function updateBalance(userId: string, amount: number) {
      // Use an atomic increment to prevent race conditions
      await db.users.update(userId, {
        balance: { increment: amount }
      });
    }
    

    Regression Test

    1. Initialize a user with a balance of 100.
    2. Fire two concurrent calls to updateBalance(userId, 50) using Promise.all.
    3. Expected: Final balance is 200.
    4. Actual (Original Code): Final balance is 150.

    Next steps

    • Verify if your database driver supports atomic increments (e.g., Prisma, Mongoose, or raw SQL SET balance = balance + ?).
    • Review other financial or counter-based logic in the codebase for similar patterns.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Manual code reviews often miss subtle race conditions, security vulnerabilities, and N+1 query patterns. Traditional linters catch style issues but fail to detect logic flaws that lead to production outages.

    What it does

    • Identifies logic defects like off-by-one errors, broken state transitions, and null pointer risks.
    • Conducts deep security audits for injection, unsafe deserialization, and cryptographic misuse.
    • Analyzes performance bottlenecks including blocking I/O and unnecessary memory allocations.
    • Generates targeted regression tests to reproduce and verify fixes for identified bugs.

    Frameworks & tools

    Supports TypeScript, JavaScript, Python, Go, Rust, Java, Kotlin, C/C++, and SQL. Specific patterns for React, Next.js, and backend API architectures.

    Why this beats prompting it yourself

    This skill follows a structured multi-mode engine that forces evidence-based reasoning rather than speculative guessing. It produces prioritized scorecards and regression tests that standard LLM prompts typically overlook.

    Use cases

    • Reviewing complex Pull Requests for hidden regressions and architectural violations.
    • Debugging production stack traces to find the root cause and a safe remediation.
    • Performing security-first audits on sensitive authentication or data handling logic.
    • Identifying test gaps in critical business modules to improve reliability.

    Known limitations

    Cannot execute code or verify benchmarks in a live environment. Performance and security claims are based strictly on source analysis and supplied context.

    Requires source code or diffs. Cannot execute code or provide real-time benchmarks. Scope is limited to provided project context.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Trust & safety

    Security scan

    Security scan passed 1 month ago

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    No special permissions declared or detected

    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill uses a multi-mode reasoning engine to identify complex logic flaws, security vulnerabilities like SQL injection, and performance issues like N+1 queries that standard linters and basic prompts often miss.

    It supports a wide range of languages including TypeScript, JavaScript, Python, Go, Rust, Java, Kotlin, C/C++, and SQL, with specific optimization for React and Next.js frameworks.

    You receive the specialized code review agent configuration, optimized reasoning patterns for debugging, and a structured reporting template for prioritized bug scorecards.

    While it cannot execute code in a live environment, it generates targeted regression tests that you can run locally to verify the proposed bug fixes.

    Yes, once you integrate the skill into your compatible AI platform, you can point it at specific Pull Requests or code blocks to receive an automated, security-focused audit.

    Updates are released periodically to include new security patterns and support for additional language features, ensuring the agent stays current with modern coding standards.

    New in Testing & Debugging