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Found 20 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.
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.
Incrementally update reverse-engineering docs based on git changes since they were last generated. Reads the commit hash from .stackshift-docs-meta.json, diffs against HEAD, analyzes only the changed files, and surgically updates the affected docs. Saves time and cost compared to full regeneration.
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.
Runs a Trailmark structural review gate over a branch, pull request, fix commit, release diff, or git ref range to detect new entrypoints, new tainted paths, removed validation or authorization calls, privilege-boundary drift, blast-radius growth, complexity growth, and newly reachable sensitive sinks. Use when reviewing a PR, branch, remediation commit, or release diff where graph-level security regressions should be checked before merge.
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.
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.
Optional skill. Reconstruct a human-review-preparation file from an existing pull request, merge request, branch diff, or commit range in a repository the user trusts. Use when the user wants retrospective understanding of already-implemented changes, AI-side assessment and recommendations, and an optional provider-specific sharing variant written to a local file when needed.
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.
Generate conventional commit messages based on git diff analysis. Use when you need to create well-structured commit messages following conventional commit format.
Analyzes git diff and commit history to write PR title and description based on the project's PR template.