Cloud, CI/CD, monitoring, and deployment (6.8K skills)
Configure Hermes to run AI models through Actual Computer on your own hardware. Set up either the hosted relay or a local connection, select models, verify responses, and troubleshoot request errors or empty output.
Manage Docker containers, images, storage volumes, and networks with standard commands. Start multi-service applications with Docker Compose, investigate failures through logs, check disk usage, and review Dockerfiles for improvements.
Monitor RSS feeds, JSON APIs, and GitHub activity at regular intervals. Included scripts track previously seen item IDs and output only new entries, letting an agent report updates while staying silent when nothing has changed.
Connect a remote Hermes gateway to MCP servers that require OAuth, a browser-based authorization process. The skill covers dashboard access, manual token setup when needed, and diagnosis of expired tokens or revoked sessions.
Prepare code changes for sharing by merging the base branch, running tests, and reviewing the diff. Update VERSION and CHANGELOG, then commit, push, and create a pull request, a proposal to merge the changes.
Merge an existing pull request, wait for automated checks and deployment, then verify production health with canary checks, targeted checks for problems. Continue the release workflow after /ship has created the pull request.
Monitor a live app after deployment for console errors, slower performance, and page failures. Periodic screenshots and comparisons with pre-deployment baselines help identify anomalies and check whether the release is behaving as expected.
Configure deployment, the process of publishing an application, for /land-and-deploy. Identify the hosting platform, production URL, health check endpoints, and status commands, then save those settings in CLAUDE.md for future deployments.
Update gstack by detecting how it is installed, refreshing registered installations, and handling project copies and version migrations. Receive a summary of user-facing changes, along with installation-specific recovery information if an upgrade fails.
Review Caveman Cloud experiment states, evaluation results, and safety checks to recommend a supported next action. Identify missing or failing evidence and explain execution blocks; the current agent interface reads experiment data without changing its lifecycle state.
Connect an application's LLM calls through the Caveman Cloud gateway to measure usage and cost without changing request content. The skill updates connection settings and verifies the integration with one small, real provider request.
Prepare a production release with checks for code quality, security, performance, accessibility, and infrastructure. Plan monitoring, gradual feature exposure, and rollback steps, then use release metrics and reliability limits to guide rollout decisions.
Add logs, metrics, traces that follow requests across services, and actionable alerts to production features. This skill guides signal design, request identification, response instructions, and checks that the collected data can explain failures.
Set up automated checks and deployment workflows with GitHub Actions. Covers tests, type checks, builds, security audits, preview deployments, staged releases, and rollback plans, with guidance for diagnosing failures and reducing pipeline runtime.
Investigate slow Paperclip runs, page requests, and CI suites using Honeycomb traces, which show timed operations. Find relevant traces, separate overlapping work, identify dominant delays, and configure optional tracing or add missing measurements.
Set up a Paperclip maintenance bot that applies a chosen skill to a repository and opens pull requests. Configure its agent, schedule or event trigger, work limits, reviewers, and readiness checks before activation.
Coordinate a complete Paperclip release, from candidate verification and canary testing to stable npm publication and GitHub Release creation. Track release notes, Docker smoke tests, announcement follow-up, and linked content cases when Cases are enabled.
Start and repair isolated Paperclip development workspaces through managed services. Restore a full database clone when needed, then verify login, populated data, health, service visibility, and whether the process using the port belongs to the intended workspace.
Investigate failing or pending checks on the latest commit of a GitHub pull request. Reproduce actionable failures, fix and push changes, then recheck remotely until checks pass or a specific blocker is reported.
Publish a folder of static HTML and assets to the configured Paperclip S3/CloudFront host. Validate the folder before upload, obtain a persistent public URL, and update an existing page from its original publishing directory.
Create a one-page service operations guide in HTML. It organizes service details, alerts and first responses, dashboard links, procedures with copyable commands, an on-call schedule, and an incident checklist so teams can find operational instructions together.
Monitor a shipped release by checking published packages, live services, installed plugins, and late CI results or user reports. Verify regressions, prepare authorized fixes, and report release health with evidence and any remaining verification gaps.
Delegate a coding task to a subagent that runs build, merges the ready pull request, and continues from the updated main branch into release, connecting implementation and release work in one automated sequence.
Delegate release work to a subagent that runs the claude-mem skills version-bump and childhood in order. Use it to coordinate those two stages as a single automated task.