Working plugin for Databricks Field Engineering assets — UCO management and MCP tooling
This skill should be used when the user mentions "UCO", "use case", or "use case object" in any context — including requests to find, list, count, filter, update, add, or ask questions about UCOs. Trigger on phrases like "show my UCOs", "how many UCOs", "what UCOs does this account have", "update a UCO", "create a UCO", "UCO status", "UCO health", "stale UCOs", "UCOs for [account/AE/SA]", or any question about use case lifecycle stages.
HUMAN task management — canonical operating model for the human's work backlog. Use when setting up task tracking, selecting or creating the GitHub repository for tasks, updating task status, handing off work between sessions, or triaging backlog.
Admin access level
Server config contains admin-level keywords
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Marketplace repository for Randy's Claude Code plugins.
.claude-plugin/marketplace.json — marketplace manifestplugins/rpw-building — dev/tooling plugin (commands, skills)plugins/rpw-working — working plugin (skills, MCP config, mcp-servers/)plugins/rpw-databricks — Databricks-specific work activity plugin (commands, skills)plugins/rpw-working/raycast — starter Raycast assets for task capture workflows.claude-plugin/plugin.json per plugin; skills, commands, MCP colocated in each pluginAfter installing, run /doctor (or /getting-started or /start-here) to validate your environment. It checks required tools, plugin versions, and MCP server configuration.
Re-run the install command to pull the latest plugin versions:
claude plugin marketplace add rpw-agent-marketplace
The /doctor command includes a plugin freshness check that warns when installed versions are behind the marketplace.
docs/architecture/plugin-boundaries.mddocs/process/context-mode-activity-pattern.mddocs/process/required-plugin-stack.mdmake verify
Prerequisite: install uv so make verify can run uv run ....
For local runtime configuration, prefer environment-specific files:
template.env to document required variables and structure.dev.env, test.env, and prod.env local-only (ignored by git).APP_ENV=dev|test|prod (default: dev).This pattern is implemented in MCP server startup wrappers (run_mcp.py) under plugins/rpw-working/mcp-servers/.
Publish a filtered copy of this repo to a public GitHub repo:
make publish-setup # First-time: create public repo + clone locally
make publish-dry-run # Preview what would be published
make publish-public # Publish (scan, filter, sync, push)
Exclusions are configured in .public-publish.yml (rpw-databricks, .beads, .env files, hooks, local settings). The publish script runs secret scanning on both source and output.
make public-release-scan checks for blocked file paths and secret patterns.make marketplace-release includes a confirmation gate via make public-release-gate.PUBLIC_REPO_RELEASE_CONFIRM=I_ACKNOWLEDGE_PUBLIC_REPO_RELEASEThis repo uses a single required plugin stack for onboarding (no personas/profiles):
superpowers, beads, code-context, context-moderpw-building, rpw-working, rpw-databricksRun:
uv run python scripts/enable_required_stack.py
This writes to .claude/settings.local.json by default.
YYYY.MM.DDNN (NN is zero-padded intra-day sequence)..claude-plugin/marketplace.json.plugins/*/.claude-plugin/plugin.json) must define a version field matching their marketplace.json entry.scripts/bump_marketplace_versions.py (see make version-bump and make production-merge-helper).docs/decisions/ADR-001-calendar-first-versioning.md.Dev and tooling plugin — /build command, /doctor setup, MCP standards, cmux integration
npx claudepluginhub randypitcherii/rpw-agent-marketplace --plugin rpw-workingClaude Code skill pack for Databricks (24 skills)
Centralized Claude Code configuration: Docker-first guards, permissions, MCP gateway, and workflow skills
Databricks development toolkit with skills for data engineering, ML, and AI agents plus MCP tools for direct Databricks operations
Manage MCP servers - discover, analyze, execute tools/prompts/resources. Use for MCP integrations, capability discovery, tool filtering, programmatic execution, or encountering context bloat, server configuration, tool execution errors.
Databricks skills for CLI, Apps, Unity Catalog, Model Serving, Declarative Automation Bundles (DABs), and more.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.