GitLab container registry operations via API. ALWAYS use this skill when user wants to: (1) list container repositories, (2) view/delete image tags, (3) clean up old images, (4) manage Docker registry.
Search, browse, and analyze CERN GitLab repositories for HEP code, documentation, and examples. Use this skill whenever the user mentions CERN GitLab, LHCb/ATLAS/CMS code, HEP software stacks, or wants to find code patterns, inspect build systems, read READMEs, search issues, or explore releases in gitlab.cern.ch…
MCP server for CERN GitLab - code discovery, documentation access, and usage examples for HEP projects. Runs locally from the cerngitlab-mcp Python package.
Instructions for detailobsessed/efficient-gitlab-mcp, covering efficient gitlab mcp, quick reference, architecture, progressive disclosure and adding a new tool.
GitLab MCP Server with progressive disclosure - 2 meta-tools, 90% token reduction. Runs locally from the efficient-gitlab-mcp-server npm package. Needs 2 environment variables to run.
MCP server for self-hosted GitLab — pipelines, schedules, branches, merge requests and repository files. Runs locally from the gitlab-ci-mcp Python package. Needs 4 environment variables to run.
Instructions for Dropelikeit/pr-comments-resolver, covering pr comments resolver — development guide, project structure, plugin format, conventions and adding a new skill.
Use when resolving unresolved PR or MR review comments, working through reviewer feedback, or addressing code review threads on GitHub, GitLab, Bitbucket Cloud, or Azure DevOps repositories.
Scheduled sweep of incomplete Asana tasks assigned to you — triage into auto/ask/skip, dedupe against existing work, then call asana-to-harness to open GitLab issues that trigger an AI coding harness. Built for headless scheduled runs (claude -p); also runs interactively, with --dry-run support.
Turn one Asana task into an implementation plan for an AI coding harness, open a GitLab issue with the plan as its description, and leave a trigger comment (e.g. @claude). Used standalone ("turn this Asana task into a harness issue") or invoked by the asana-sweep skill.
Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or…
Builds Nango Functions in a checked-out Zero YAML TypeScript Nango project using local files, index.ts registration, nango dryrun, generated tests, and optional nango deploy via CLI. Use when creating, updating, validating, testing, or deploying Nango actions or syncs locally in a repo. This content overlaps with…
Builds Nango Functions without a checked-out Nango project by using the Nango /functions compile, dryrun, dryrun status, and deployment APIs with NANGOSERVERURL and NANGOSECRETKEY. Use when creating, updating, validating, testing, or deploying Nango actions or syncs remotely via API or single-file payloads. This…