analyze_current
Read and understand the current baseline implementation. Extract all relevant information about the existing approach without modifying anything, and record…
Perform structured code reviews with actionable feedback. Use when a user asks to review code, check code quality, find bugs, audit security, improve performance, or assess maintainability. Trigger when user says things like "review this code", "check for bugs", "is this code
$ npx -y skills add Upsonic/Upsonic --skill code-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/code-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Perform structured code reviews with actionable feedback. Use when a user asks to review code, check code quality, find bugs, audit security, improve performance, or assess maintainability. Trigger when user says things like "review this code", "check for bugs", "is this code
name: code-review description: Perform structured code reviews with actionable feedback. Use when a user asks to review code, check code quality, find bugs, audit security, improve performance, or assess maintainability. Trigger when user says things like "review this code", "check for bugs", "is this code secure", "any issues with this", "code quality check", or pastes code asking for feedback. Also trigger for pull request reviews and pre-merge code checks. Do NOT trigger for writing new code from scratch, refactoring requests without review context, or general programming questions. metadata: version: "2.0.0" author: Upsonic tags: [development, quality, review, security, bugs]
Perform a structured, multi-dimensional code review. Act as a senior engineer reviewing a colleague's work — be thorough but constructive.
**Trigger conditions:**
**Initial approach:** Before diving in, understand the context: 1. What language/framework is this? 2. What does this code do? (Read it first, don't ask unless unclear) 3. Is this a snippet or full module? 4. Any specific concerns the user mentioned?
Read the entire code before making any comments. Understand:
This context matters. A quick prototype doesn't need the same scrutiny as a payment processing module.
Review across five dimensions, in priority order:
Does the code do what it's supposed to?
Check for:
Could this code be exploited?
Check for:
Will this code perform well under load?
Check for:
Can another developer understand and modify this code?
Check for:
Does the code follow project and language conventions?
Check for:
Structure your review as follows:
Issues that must be fixed — bugs, security vulnerabilities, data loss risks.
For each issue:
Issues that should be fixed — performance problems, potential bugs, poor error handling.
Same format as critical issues.
Nice-to-have improvements — readability, style, minor refactors.
Keep these brief. Don't nitpick.
Acknowledge good patterns, clean abstractions, thorough error handling, or clever solutions. This matters — it reinforces good practices and shows you read the code carefully.
Read and understand the current baseline implementation. Extract all relevant information about the existing approach without modifying anything, and record…
Define the comparison metrics and extract baseline values from the current implementation. Record them as a structured JSON entry so downstream phases and…
Compare baseline and new implementation results. Produce the machine-readable final report `result.json`, update `experiments.json`, and append a row to…
Set up and manage the experiment folder structure. This is Phase 0 — it runs before any analysis begins. All bookkeeping files are JSON (never markdown).
Create a new Jupyter notebook implementing the method from the research paper, using the same data as the baseline. Record implementation details and measured…