Cloud, CI/CD, monitoring, and deployment (6.8K skills)
Deploy n8n on a Linux server using Docker Compose and Caddy for automatic HTTPS. Choose a single instance or queue workers, configure secrets and Python task runners, and follow procedures for updates, backups, and recovery.
Work across multiple n8n instances through one MCP connection, the link used by an agent to call tools. Specify each operation’s target, verify where credentials will be stored, and recover when requests reach the wrong environment.
Troubleshoot Feishu plugin authorization and permission problems using an FAQ and a diagnostic command. Check account configuration, API connectivity, app permissions, and user authorization, then review a report with issues and suggested fixes.
Guides LoopX project setup and repair, including goal configuration, shared registry synchronization, stale dashboard status, and command-line routing issues. It distinguishes project lifecycle maintenance from ordinary task execution and directs each operation to its relevant procedure.
Prepare and publish DeepChat releases through its project-specific workflow. Update versions and bilingual changelogs, run release checks, manage release branches and tags, and resume unfinished releases before publishing after release PR approval.
Check whether an Apache Hudi metadata table is synchronized, lists stored files consistently, and compacts on schedule. Interpret a read-only health report to identify record index sizing problems and recommend specific next steps.
Investigate failed Apache Hudi jobs using stacktraces, configuration, and logs. Identify known failure patterns, explain the failing phase and available evidence, and provide ordered mitigation steps once the necessary details are confirmed.
Check whether Apache Hudi table maintenance is keeping pace with incoming data. Runs a read-only utility, interprets its JSON report, and explains unhealthy or skipped checks with concrete next steps.
Check whether an Ouroboros update is available and upgrade after the user chooses to proceed. The native updater preserves the installation manager, environment, and optional dependencies, then provides restart guidance for the host integrations.
Stop stuck Ouroboros executions or background jobs by ID, or cancel all running and paused executions in the current project. It reports whether cancellation is complete or has been requested, with guidance for checking the final status.
Manage Ouroboros settings through a browser interface or chat commands. Choose agents and models globally or for individual stages, change the LLM backend, review saved settings, and restore the configuration from before the last change.
Check release readiness by reviewing tests, type checks, linting, builds, security findings, documentation, and environment settings. Get a report separating deployment blockers from warnings, plus action items and checks for post-deployment health and rollback preparation.
Deploy an application to an environment that has already been configured. Use it when the destination is established and the next task is to put the application into that environment.
Diagnose command failures before attributing them to sandbox restrictions, which limit access to files and networks. Check execution methods, command matching, and network behavior, then prepare an evidence-based report for the person responsible for settings.
Prepare a branch for a pull request by running local tests, checking types for Node projects, pushing commits, and showing the CI pipeline link. Failed checks stop the workflow before the push.
Check CI, the automated checks run on code changes, for the current branch alongside recent commits. Supports GitLab CI and GitHub Actions, with optional pull request or merge request numbers and links when command-line tools are unavailable.
Take an existing pull request through automated check results, user approval, merging, deployment verification, and a production health check. Report outcomes and timings, with investigation or rollback options when deployment problems appear.
Monitor a live application after deployment and compare it with a saved baseline, a record of its earlier state. Check page responses, loading times, and new errors, flag persistent changes, and produce a per-page health report.
Push the current Git branch and get a link to its GitLab CI or GitHub Actions runs. The workflow checks for uncommitted changes and blocks direct pushes to main, master, and production before proceeding.
Register a deployed agent with Gemini, choose the appropriate registration method, and troubleshoot setup problems. Also covers managing agents and registering MCP servers, which expose tools to agents, in Google Cloud Agent Registry.
Plan and carry out agent deployments on Google Cloud using agents-cli. The guide covers deployment targets, permissions, secrets, automated build and deployment pipelines, verification, and recovery procedures for agents built with supported frameworks.
Set up monitoring for deployed agents to inspect execution paths, latency, and model interactions. It explains Cloud Trace, prompt and response logging, BigQuery analytics, and external monitoring integrations, with checks for missing data and unwanted content capture.
Guides Kaku’s macOS release process from prerequisite checks through building, signing, Apple notarization, and GitHub publication. It covers stable releases, Homebrew tap updates, rolling Nightly previews, and resuming failed stages using existing release scripts.
Inspect production AI agents in FailproofAI Cloud using the fp CLI. Review errors, run histories, quality scores, and usage, then manage issues, audits, user access, and scoped API keys for the team's deployment.