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Found 13 Skills
Run vet immediately after ANY logical unit of code changes. Do not batch your changes, do not wait to be asked to run vet, make sure you are proactive.
Use when the user asks to perform a code review, review code changes, analyze a diff, or audit code quality. Runs a structured review of git diff output covering security, correctness, performance, maintainability, and style. Produces a markdown report saved as a .md file named after the current branch.
Auto-generates conventional commit messages from git diffs with tiered format enforcement. Analyzes staged changes to produce meaningful commit messages following Conventional Commits specification.
Runs .continue/agents checks locally against the current diff, simulating the GitHub PR checks experience. Use when the user says /check to review their changes before pushing.
Analyzes git diff and commit history to write PR title and description based on the project's PR template.
Generate conventional commit messages based on git diff analysis. Use when you need to create well-structured commit messages following conventional commit format.
Generate conventional commit messages automatically. Use when user runs git commit, stages changes, or asks for commit message help. Analyzes git diff to create clear, descriptive conventional commit messages. Triggers on git commit, staged changes, commit message requests.
Validates code changes against DeepRead's mandatory patterns and standards defined in AGENTS.md. Use this after writing or modifying code to catch violations before committing.
Code review of current git changes, compare to related plan if exists, identify bad engineering, over-engineering, or suboptimal solutions. Use when user asks to review changes, check git diff, validate implementation quality, or assess code changes.
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Removes AI-generated code slop from git diffs to maintain code quality
Generate and create pull request descriptions automatically using GitHub CLI. Use when the user asks to create a PR, generate a PR description, make a pull request, or submit changes for review. Analyzes git diff and commit history to create comprehensive, meaningful PR descriptions that explain what changed, why it matters, and how to test it.