GitLab plugins

Manage GitLab projects by accessing repositories, creating and reviewing merge requests, monitoring CI/CD pipelines, handling issues, and updating wikis through remote API integration with a personal access token.

Generate multi-stage CI/CD pipelines in YAML for GitHub Actions, GitLab CI, Jenkins, and CircleCI. Automate workflows covering linting, testing, Docker image builds/pushes, security scans, and gated deployments to staging/production on Kubernetes.

Set up CI/CD pipelines for GitHub Actions, GitLab, or Jenkins; containerize apps with Dockerfiles, docker-compose, and Kubernetes manifests; automate changelogs in Keep a Changelog format; prepare semantic releases; deploy hotfixes; and rollback deployments via slash commands.

Debug and fix CI/CD pipeline failures in GitHub Actions, GitLab CI, and Jenkins. Analyze logs or URLs to identify root causes, flakiness, and patterns; get fix suggestions with config diffs and confidence scores. Automatically apply minimal changes, add caching or notifications, validate syntax, and commit with explanations.

Generate DevOps automation scripts for CI/CD pipelines, deployments, and infrastructure tasks in GitHub Actions, GitLab CI, or shell formats with safety guards. Create health check scripts to verify service availability, standardize status reporting, set up alerting, enable cron or Kubernetes scheduling, and include documentation.

Deeply analyze open-source Git repositories on GitHub or GitLab to generate professional architecture reports featuring Mermaid diagrams, business insights, design rationale, and critical evaluations for studying frameworks, comparing projects, or architecture research.

Automate Git release workflows: inspect commits since the last tag in an interactive, author-aware table with git show details, then create releases via semver bump detection, PR/commit-based changelog generation, preview, tagging, and publishing to GitHub, GitLab, or Gitea.

Automate GitHub PR reviews for architecture, tests, and scope; interactively annotate git diffs, apply AI fixes in feedback loops until approved; enforce concise writing style for issues, PRs, commits, and reviews without AI-speak.

Automate Git-centric development workflows: generate conventional commit messages from changes, prepare PRs with quality gates and self-reviews, fix review feedback across steps from triage to validation, consolidate ephemeral docs into permanent ones, update tests and tutorials, bump versions with changelogs, and manage dependencies in Python/JS/Rust/Go repos.

Provides foundational infrastructure patterns and pipeline building blocks for Claude Code plugins: authentication, supply-chain security audits, error recovery, testing standards, quota tracking, service registration, document ingestion, and git-platform detection. Includes CLI commands for plugin cache refresh and attestation-based trust verification.

Use GitLab CLI (glab) to manage issues, merge requests, CI/CD pipelines, repositories, and other operations directly from the terminal, enabling efficient command-line workflows for GitLab projects.

Orchestrate multi-agent code reviews, async agent delegation, quality enforcement, and project memory learning. Includes MCP servers for documentation retrieval and DeepWiki proxying, hooks for event dispatch, and a CI/CD agent that monitors pipelines and spawns fixer agents for lint, test, and build failures.

Orchestrate AI-driven development workflows across multiple coding agents — delegate code review to external AI agents, enforce structured planning and bug-fix protocols, manage hooks/plugins/skills/subagents/MCP servers for Claude Code/Codex CLI/OpenCode, research via Semantic Scholar, clean up macOS or Windows systems, and maintain naming consistency with a project thesaurus.

Structure software projects into context-driven tracks: scaffold setups, generate specs and plans from project docs, implement tasks via AI agents with git snapshots, review code for quality/security/test coverage, track progress, manage skills/snippets/patterns, and revert via git history.

Sets up a complete AI-assisted development workflow: bootstraps CLAUDE.md, formatters, and test infrastructure, then guides structured brainstorming, TDD cycles, code review, refactoring, test coverage, and git operations — all tailored to your actual codebase.

Configure and optimize GitLab CI/CD pipelines by editing .gitlab-ci.yml files with CI steps, Docker-in-Docker workflows, caching strategies, and local testing via gitlab-ci-local. Author GitLab Flavored Markdown READMEs and Wikis using alerts, Mermaid diagrams, and references. Set up secure project access tokens as masked CI/CD variables for publishing.

Automates CI/CD pipeline generation from project stack detection, validates Dockerfiles and workflows, audits dependency security, and runs zero-downtime deployment preflight checks.

Enforce a structured Context-Driven Development loop: draft specs and plans, enforce TDD and code coverage, run multi-dimensional code reviews, generate deployment checklists, track status, and produce standup summaries from git and Jira activity.

Practice Test-Driven Development with AI guidance: activate TDG to detect red/green/refactor phases via scripts, generate incremental tests and matching code, refactor incrementally, and commit atomically to git with conventional messages, issue links, and verification. Auto-configure projects in JS/Python/Go/Rust.

Enforce Qodo coding standards and resolve PR review feedback directly in your local development workflow. Load relevant rules via semantic search before writing code, then fetch PR issues, apply fixes interactively or in batch, and reply to inline comments across GitHub, GitLab, Bitbucket, Azure DevOps, and Gerrit.

Author and optimize GitLab CI/CD pipelines with structured job configuration, DAG-based execution, artifact caching, and secure secret management using Vault and cloud provider integrations.

Manage stacked diffs across GitHub and GitLab using git-gud. Create dependent PRs/MRs, sync stack updates, check CI/review state, and land approved changes safely through an automated CLI workflow.

Guides feature development from brainstorming through implementation, code review, and pull request creation, following Very Good Ventures engineering standards and Conventional Commits.

Run GraphQL Inspector to diff schemas, detect breaking and dangerous changes, validate query complexity and depth, and enforce schema governance in CI pipelines (GitHub Actions, GitLab CI) with automated PR comments.

Build and maintain Python 3.11+ CLI applications with Typer/Rich, following TDD workflows with pytest, modern type hints, and pyproject.toml packaging. Includes code review, debugging, test analysis, CI/CD setup, and documentation generation.

Configure Git across Windows, macOS, Linux, and WSL: set up identities, GPG signing, hooks for code quality, line endings, and safe pushes; troubleshoot issues; query and research GitHub issues via CLI; explore repo history and issues read-only without modifications.

Set up a structured, multi-agent development workflow with quality gates, board management, and session continuity across AI coding tools. Automate issue tracking, code review, testing, accessibility, security, and release processes through specialized agents and commands.

Automate application security testing (SAST, SCA, secrets detection) and automatically fix findings across your codebase. Integrates with CI/CD pipelines, generates compliance attestations, and provides threat modeling, SCA triage, and business-logic vulnerability analysis. Guards against writing insecure code patterns and supports multi-platform CI (GitHub Actions, GitLab, CircleCI, Jenkins, Vercel).

Delegate SDLC security workflows to AI agents that generate compliance reports with metrics visualizations and GitHub/Jira integrations, perform multi-jurisdiction privacy assessments like GDPR/CCPA, design behavioral enforcement strategies for team adoption, and architect zero-trust systems with threat modeling.

Deploy Capacitor apps via CI/CD pipelines with GitHub Actions and GitLab CI, publish to Apple App Store and Google Play Store using guided checklists and configurations, and audit iOS apps for Apple compliance including privacy manifests, entitlements, and rejection patterns before submission.

Manage GitLab projects directly from the CLI: create issues and merge requests, review code changes with pipeline status, monitor CI/CD pipelines in real time, and perform code search across projects.

Semantically search codebases using natural language queries and dependency graphs, then perform tasks like root cause analysis, safe refactoring, PR review, codebase onboarding, and commit message generation with blast radius awareness.

Orchestrate multi-wave development sessions with automated planning, quality gates, VCS integration, and persistence — chaining session-start through wave-execution to session-end with kill switches, health monitoring, and cross-repo dashboards for GitLab/GitHub projects.

Generate optimized enterprise CI/CD pipelines as YAML workflows for GitHub Actions or GitLab CI, tailored for Node.js projects with QA, build, security, and deployment stages to streamline DevOps automation.

Audit documentation against code for drift, sync docs after code changes, optimize CLAUDE.md and SKILL.md prompts, validate GLFM/Markdown formatting, and summarize files, URLs, or images with source-attributed citations.

Manage Git worktrees with the wt CLI to enable parallel development: create, checkout, list, and remove worktrees for branches, GitHub PRs, and GitLab MRs; configure layouts, strategies, and hooks for organized multi-repo workflows.

Author, analyze, test, secure, and deploy cross-platform PowerShell 7.5/7.6 modules and scripts with Pester, migrate for 2025 deprecations like MSOnline to Microsoft.Graph and WMIC replacements, generate GitHub Actions/Azure DevOps CI/CD pipelines, and manage secrets via SecretManagement vaults.

Establish a human-on-the-loop workflow for AI-native development by defining structured design contracts, automating parallel execution with human checkpoints, enforcing code review and TDD, and managing git workflows from planning through merge.

Manage the full DevOps lifecycle from infrastructure provisioning and CI/CD pipeline setup to production deployments with blue-green, canary, or rolling strategies, automated rollbacks, and health monitoring.

Enforce expert-level programming principles during refactoring, testing, API design, code review, and commits using rigid checklists distilled from '97 Things Every Programmer Should Know'.

Orchestrate full developer workflows: implement tasks via TDD in isolated git worktrees, safely migrate Android/Kotlin code (Views→Compose, RxJava→coroutines, Java→Kotlin, to KMP), generate/execute test plans and exploratory QA on web/mobile apps, create/manage GitHub/GitLab PRs through CI/CD monitoring, reviews, and fixes to merge-ready state.

Supercharges Claude Code with a structured engineering workflow: triage and refine issues, prototype designs, test-drive vertical slices, debug regressions, refactor for cohesion, and hand off context between agent sessions.

Run a structured, multi-phase development workflow with planning, milestone decomposition, audit gates, quality scoring, patch management, and release automation — all managed through a local pipeline state and CLI commands.

Install, initialize, configure, and update Pappardelle workspaces in Git repositories using interactive slash-command wizards and TUIs. Set up VCS hosts like GitHub/GitLab, Jira integration, profiles, hooks, keybindings; generate YAML configs; monitor active worktree spaces by status (FIRE, WORKING, IDLE) for Claude development sessions.

Scaffold a scheduled 'doctor' agent that continuously audits application health by running runbooks and scanning logs, then autonomously opens pull requests for code-fixable issues and files deduplicated tickets for the rest

Batch review GitHub PRs and GitLab MRs via live tmux dashboard spawning isolated sessions per PR, delegate peer reviews gathering context for errors/types/tests with style-matched comments, self-review code changes using visual diff viewer to add line-specific comments for git edits, and automate follow-ups classifying threads with status summaries and approve suggestions.

Automate end-to-end SDLC workflows in GitHub/GitLab repos using slash commands and agents: generate detailed specs/test plans, manage git branches/commits/PRs, implement features via TDD, resolve review comments, perform performance/architecture analysis, and handle setup/testing.

Delegate deployment engineering to AI agents that design CI/CD pipelines with GitHub Actions, GitLab, and Jenkins; implement GitOps via ArgoCD/Flux; automate Terraform IaC for multi-cloud AWS/GCP/Azure setups; orchestrate Docker containers and Kubernetes for zero-downtime deployments with security scanning.

Generate comprehensive documentation from codebases: API specs (OpenAPI, GraphQL), architecture diagrams (Mermaid), technical references, tutorials, changelogs, and Architecture Decision Records, with CI/CD automation for publication.

Generate AI media (music, images, video) via AceDataCloud's unified API, integrating models like Suno, Midjourney, Luma, and Sora, while also managing cloud infrastructure (Tencent Cloud), productivity tools (Google, Notion, Slack), and social platforms (LinkedIn, Reddit, YouTube).

Run systematic code reviews for runtime bugs in JS/TS and Python, then automate GitHub/GitLab issue-driven development by filtering PRD/feat issues, implementing them in git worktrees, and submitting auto-merge PRs/MRs.

Automate GitLab merge request reviews by fetching changed file diffs via MCP tools and analyzing for security issues, bugs, logic errors, and code quality. Manage GitLab issues through local API connections using Python subprocesses with personal access tokens.

Enforce ticket-driven Git development by validating GitHub, GitLab, Jira, or Linear tickets in commit messages and branch names before commits; document project intentions, explorations, and learnings in structured INTENT.md files; apply guided workflows with GitHub Flow, Git Flow branching strategies, conventional commits, and PR templates.

Architect CI/CD pipelines with stages for build, parallel testing, staging/production deployments, verification, monitoring, and rollbacks. Design zero-downtime strategies like blue-green, canary, rolling updates with health checks, rollback plans, and risk analysis. Review pipelines for missing stages, anti-patterns, production readiness, and safety gaps across GitHub Actions, GitLab, Jenkins.

Generate marketing-oriented READMEs, changelogs from git history and conventional commits, roadmaps from GitHub milestones and issues, and task-oriented user guides. Audit documentation completeness, quality score, freshness, and coverage across README, CONTRIBUTING, issue templates; auto-generate missing files and refresh based on git changes. Optimize for GEO, SEO, and AI citation with llms.txt.

Manage GitLab workflows entirely from the terminal using the glab CLI — query issues and merge requests, debug CI/CD pipelines, validate pipeline configs, navigate GitLab docs, and handle todos without leaving your editor.

Automate GitHub/GitLab pull request workflows: create PRs with formatted titles and sections, update descriptions after new commits, monitor CI builds and auto-fix trivial failures, resolve review threads, and guard against destructive git operations and credential leaks.

Project-agnostic task and release management: clone any repo, then use 8 conversational skills to create ideas, track tasks, run staged releases, generate docs, initialize configs, and update pipelines — all orchestrated by a gated CI/CD subagent framework.

Automate Jira issue management, Git release and conflict resolution, performance analysis and optimization, and Chinese documentation tasks using structured multi-stage workflows.

Coordinate multiple AI agents as a team to build, test, debug, and review code through structured workflows with human approval gates, agent handoffs, and automated context tracking across sessions.

Automate GitLab workflows using glab CLI: create and link labeled issues to parents, generate branches/commits/pushes/MRs with auto-merge on pipeline success, integrate AI code reviews to auto-merge clean MRs or generate TDD fix plans from top findings.

Follow interactive guides to integrate Infisical secrets management into CLI dev environments, Docker builds and runtime, CI/CD pipelines with GitHub Actions or GitLab CI, Kubernetes Operator, and SDKs for Node.js, Python, Go, Java, .NET, Ruby—including machine identity auth setup.

Orchestrates AI-driven multi-agent development workflow across multi-repo projects, from story refinement and requirements analysis to code implementation, review, testing, and PR creation, with automated guardrails and human approval gates.

Automate the full issue-to-pull-request workflow across GitHub, Linear, and GitLab by fetching issue details, creating branches, committing changes, and opening PRs. Refines brief descriptions into structured issues and enforces prerequisite checks for safe execution.

Automates Git Flow workflows: create commits, branches, pull requests, and merge requests on GitHub and GitLab, with structured PR/MR reviews and a status report for branch management.

Run guided interactive morning and evening reviews that scan Calendar events, clear Things inbox, triage GitHub, GitLab, and Linear notifications, and reorder your Today list to kickstart focused work.

Automate end-to-end software engineering workflows: orchestrate git feature flows from branching/linting/testing/committing to merge requests/issues; conduct code reviews, security audits, and debugging; generate architecture/docs/templates; integrate Stripe/PayPal payments; ensure license compliance.

Streamline daily git workflows: inspect repo context (GitHub/GitLab platform, default/current branch, status, ahead/behind, worktrees); switch to default branch (main/master) and pull latest changes, reporting prior branch; list active worktrees with paths, branches, and types.

Manage NIST OSCAL compliance documents end-to-end: author, assemble, validate, and convert Security Plans (SSP), Profiles, Catalogs, Component Definitions, Assessment Plans, and POA&Ms using the Compliance Trestle CLI and interactive agents. Supports Jinja2 templating, markdown governance, multi-repo CI/CD pipelines, and tasks for importing CSV, XLSX, XCCDF, and CIS benchmark data into OSCAL format.

Automate safe, conventional Git commits after task completion: detects tickets from GitHub, GitLab, or Jira; generates semantic messages; runs branch protection checks; requires user confirmation before local commit—never pushes to remote.

Act as expert vmkteam Go developer handling full SDLC for API services: scaffold projects with PostgreSQL repos and zenrpc, decompose and resolve YouTrack tasks end-to-end, perform multi-persona GitLab MR code reviews, automate CI/CD deploys to Nomad, monitor Prometheus/Sentry/Grafana/Loki metrics/logs/errors, investigate production incidents, generate RPC clients, and run Playwright browser automation.

Run adaptive autonomous SDLC workflows that orchestrate agent teams to implement Python features via enforced TDD/BDD cycles with pytest-bdd scaffolding, git worktree isolation for parallel tasks, Beads CLI for dependency-tracked issue management, ruff/mypy/pytest verification pipelines, documentation updates, PR creation, and automated merges.

Automate GitLab merge request reviews by fetching changed file diffs via MCP tools and analyzing them for security issues, bugs, logic errors, and code quality. Connect to GitLab API to manage issues locally as a Python subprocess using your API URL and personal access token.

Manage GitLab DevOps workflows directly from Claude — create merge requests, run CI/CD pipelines, track issues, and browse repositories without leaving the chat.

Offline search and auto-updating documentation for Claude Code — fetches official docs from code.claude.com, indexes them locally, and answers questions about features, configuration, hooks, plugins, IDE integration, and CI/CD with citations.