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.

Run DevSecOps workflows from Claude Code: review pull requests for release readiness, scan code for vulnerabilities, execute penetration tests, investigate cloud incidents, and remediate security findings using AWS DevOps and Security Agents.

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 shared infrastructure and pipeline building blocks for Claude Code plugins, including authentication patterns, content sanitization, error recovery, service registration, quota tracking, supply chain security auditing, and cross-plugin testing standards.

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 entire software engineering workflows through a unified agent marketplace: delegate subagents for architecture, code review, debugging, refactoring, testing, documentation, and CI/CD triage, with automated quality gates, project memory, and an MCP server for metrics, RAG, and DeepWiki integration.

Manage the entire lifecycle of AI coding agents across Claude Code, Codex CLI, OpenCode, and Gemini — configure settings, hooks, MCP servers, skills, subagents, and plugins; audit repositories; enforce planning and bug-fix protocols; and orchestrate multi-agent second opinions, all while keeping your machine healthy on macOS and Windows.

Sets up a project for AI-assisted development with optimized CLAUDE.md files, coding guidelines, formatter hooks, and code-quality agents — then guides structured brainstorming, spec-driven design, TDD cycles, code review, refactoring, test coverage, and git workflows (branching, commit, PRs) tailored to the actual codebase.

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.

Audit and improve PHP codebases by analyzing architecture (DDD, CQRS, Event Sourcing, Clean/Hexagonal), detecting security vulnerabilities (OWASP Top 10), code smells, and test coverage gaps. Generate production-ready Docker setups, CI/CD pipelines, and PHP components following design patterns and PSR standards.

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.

Automate CI/CD pipeline generation from your project stack for GitHub Actions, GitLab CI, or Bitbucket, validate Dockerfiles and workflows for security and best practices, and run production readiness preflight checks with zero-downtime deployment strategies.

Enforce a structured, context-driven development workflow: spec and plan before coding, track progress with TDD, review code against architecture, manage incidents, and gate deployments with checklists.

Enforce organizational coding rules and resolve PR review issues directly in your agent. Loads relevant Qodo rules via semantic search before writing or editing code, then fetches PR review feedback from GitHub, GitLab, and other platforms to apply fixes interactively or in batch.

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.

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.

Plan, implement, and ship software features using AI-guided workflows that enforce Very Good Ventures best practices: from collaborative exploration and structured planning to code generation, quality review, git operations, and pull request creation.

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.

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.

Orchestrate agentic coding workflows across multiple AI coding tools from a single canonical source — define agents, skills, rules, commands, and hooks that enforce quality gates for security, testing, accessibility, maintainability, and observability throughout development, review, and release.

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.

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.

Run structured AI-assisted development sessions with automated planning, quality gates, and VCS integration. Manage session lifecycle (start, plan, execute waves, end), integrate with GitLab/GitHub, run code quality audits, generate documentation, and enforce safety checks.

Agentic software delivery system that guides project planning, spec writing, code implementation, code review, quality enforcement, documentation updates, and pull request management through a structured multi-agent workflow.

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.

Routes documentation auditing, authoring, and optimization to specialist agents: audits docs-code drift, syncs docs after code changes, optimizes AI prompts and CLAUDE.md/SKILL.md files for Anthropic best practices, validates GLFM/Markdown formatting, and summarizes files/URLs/images with fidelity enforcement.

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.

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'.

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.

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 including music, images, and video through AceDataCloud's unified API, with additional integrations for content publishing, cloud management, and productivity automation.

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.

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.

Create, update, and monitor pull/merge requests with formatted descriptions, auto-fix trivial CI failures and merge conflicts, review thread follow-ups, and enforce security audits before tool executions.

Manage GitLab projects, merge requests, CI/CD pipelines, and todos via the glab CLI, with automated workflows for pipeline debugging, MR creation/merging, and documentation lookups.

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

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.

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 workflow from issue to pull request on GitHub, Linear, or GitLab: register issues, create branches, commit changes, and open PRs. Also transforms brief descriptions into structured issues with technical context.

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.

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.

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.

Author, validate, and transform OSCAL compliance documents (NIST 800-53, FedRAMP) using Compliance Trestle's generate-edit-assemble cycle, with markdown editing, data conversion (CSV, XLSX, XCCDF), CI/CD integration, and governance enforcement.

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.

Answer questions about Claude Code features, configuration, and usage using local docs synced from code.claude.com. Automatically update the docs to stay current, with intelligent search and citation-backed answers.