Review Python changes against shared team standards to find bugs, missing regression tests, and security issues. Findings are ordered by severity and include file names and line numbers so reviewers can locate each problem.
Review Python code for bugs, missing tests and security issues using the team's shared standards
Review the instructions the agent will receive before you install.
Check every change against the team's standards:
None and swallowed exceptions.eval, no secrets in code or logs.Report findings as a list, most severe first, each with the file and line.
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Review code for readability, security weaknesses, performance bottlenecks, test quality, and ease of maintenance. Receive findings grouped by importance, with explanations and concrete suggestions that reflect the project's context and constraints.
Write Git commit messages and pull request titles in WARP format. Combine an uppercase change type, the affected function or file, and a short imperative description into a consistent title with three bracketed sections.
Create clear, accurate charts for dashboards, data exploration, and reports. Choose chart types that fit the message, refine labels and scales, use accessible colors, and add context and annotations to help readers understand the findings.
Analyze company financial statements and ratios, then estimate value using projected cash flows and comparisons with similar businesses. Produce a valuation range, documented assumptions, scenario analysis, and risk assessment to support investment decisions.
Build and debug Python agents with Swarms, a framework for coordinating multiple AI agents. Covers tool connections, saved memory, autonomous execution, and workflow choices such as sequential steps, parallel work, specialist delegation, and combined answers.