Loading...
Loading...
Found 94 Skills
Recursive Language Models (RLM) CLI - enables LLMs to recursively process large contexts by decomposing inputs and calling themselves over parts. Use for code analysis, diff reviews, codebase exploration. Triggers on "rlm ask", "rlm complete", "rlm search", "rlm index".
[Review & Quality] ⚡⚡⚡ Two-pass code review for task completion
Request/execute structured code review: use after completing important tasks, at end of each execution batch, or before merge. Based on git diff range, compare against plan and requirements, output issue list by Critical/Important/Minor severity, and provide clear verdict on merge readiness. Trigger words: request code review, PR review, merge readiness, production readiness.
Analyzes git diffs and commit history to intelligently fill PR templates and create pull requests via gh CLI. Use when user wants to create a PR, needs PR description help, or says 'create a pull request', 'fill PR template', 'make a PR', 'open a pull request', or mentions PR creation.
Auto-generates conventional commit messages from git diffs with tiered format enforcement. Analyzes staged changes to produce meaningful commit messages following Conventional Commits specification.
Removes AI-generated code slop from git diffs to maintain code quality
Interactive Code Review: Inspect architecture, code quality, testing, and performance section by section. Can review git diff, specified files, or entire PRs. Trigger words: /code-review, review code, code review, code review
Remove AI-style code slop from a branch by reviewing diffs, deleting inconsistent defensive noise, and preserving behavior and local style.
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.
Review local git changes from 8 expert perspectives using multi-agent team orchestration. Produces a consolidated report with Critical/Important/Nice-to-have severity levels. Lightweight pre-commit or pre-push quality gate — no PR or branch push required. Use when the user asks to review local changes, check changes before committing, get a team review of working tree changes, or run a pre-commit review. Trigger phrases include "review local", "review my changes", "review local changes", "pre-commit review", "review before commit", "review before push", "team review my changes", "check my changes", "review working tree", "local code review", "review diff", "review my diff".
Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.
Diff-aware AI browser testing — analyzes git changes, generates targeted test plans, and executes them via agent-browser. Reads git diff to determine what changed, maps changes to affected pages via route map, generates a test plan scoped to the diff, and runs it with pass/fail reporting. Use when testing UI changes, verifying PRs before merge, running regression checks on changed components, or validating that recent code changes don't break the user-facing experience.