00-appkit-navigator

name	00-appkit-navigator
description	Entry-point navigator for Databricks AppKit + Lakebase development. Routes tasks to the correct skill based on keyword detection: scaffolding, plugin integration, feature building, or deployment. This is a routing skill -- it does not generate code. It directs the agent to the correct specialized skill. Use this skill as the starting point for any AppKit-related task. Triggers on "AppKit", "Lakebase app", "Databricks app", "build app", "deploy app", "scaffold app", "add plugin", "AppKit project", "agent endpoint", "wire agent", "serving plugin", "agent app proxy", "chat history", "feedback".
license	Apache-2.0
clients	["ide_cli","genie_code"]
coverage	full
metadata	{"author":"prashanth subrahmanyam","version":"1.1.0","domain":"meta","role":"navigator","standalone":true,"last_verified":"2026-06-02","volatility":"low","upstream_sources":[]}

AppKit Lakebase Navigator

Route AppKit + Lakebase tasks to the correct specialized skill.

Client awareness (Tier-1-thin). Routing is identical for every client; only the run/test/docs mechanics differ. skills/vibecoding-state detects and gates client_context; on the in-workspace agent load skills/genie-code-environment for behavior (pre-auth, serverless, page-context CLI, project-rooted artifacts — skills load from the .assistant/skills copy). The deploy verb is client-agnostic, but the local dev server / E2E test steps below are IDE/CLI-only — Genie Code verifies against the deployed app (see 03-appkit-deploy and the routed skill's deploy_note). Routed prompts open with a client-specific RULE_0 preamble; follow it.

Genie Code first-run (once). Two locations: git clone the workshop repo into your user project (/Workspace/Users/<your-username>/vibe-coding-workshop = artifact_root, git-backed so generated bundles are recognized), then copy the tree into /Workspace/Users/<your-username>/.assistant/skills/vibe-coding-workshop for skill discovery. After the copy lands, start a NEW Agent-mode chat thread (hard-refresh if skills don't appear) so Genie Code recurses the .assistant/skills copy and loads these skills. Full block: repo-root AGENTS.md ("Genie Code" section) / PRE-REQUISITES.md. Grounded in the Genie Code skills docs.

Development Lifecycle

AppKit apps follow a branch-aware development lifecycle. Each step maps to a skill or prompt:

Step 1          Step 2         Step 3            Step 4
Scaffold ──► Build ──► Deploy mock ──► Setup Lakebase
 (01)        (02)     (03-deploy)    (04-plugin-add + bundle config)
                                      │
                                      ├─► Wire Lakebase ────────────────┐
                                      │    (05-lakebase-wiring)         │
                                      │                                  │
                                      ├─► Wire Serving endpoint ────────┤
                                      │    (06-serving-wiring)           │
                                      │                                  │
                                      └─► Wire separate Agent App ──────┤
                                           (06d-agent-app-proxy)         │
                                                                         ▼
                                      Optional Chat History ──► Feedback ──► Deploy+E2E
                                      (07-appkit-chat-history) (08-appkit-feedback) (03-deploy)

Lakebase, serving endpoint wiring, and separate Agent App proxy wiring are independent branches. An app may use Lakebase only, agent chat only, or both. Choose 06 for Model Serving / Agent Serving endpoints and 06d for an agent deployed as its own Databricks App.

Use 06d-appkit-agent-app-proxy instead of 06-appkit-serving-wiring when the agent is deployed as its own Databricks App rather than a Model Serving / Agent Serving endpoint. 06d is the canonical 2-Apps path used by the root genai-agents/PROMPT-GUIDE.md.

Steps 7 and 8 are optional and apply to agent-chat apps. 07-appkit-chat-history requires Lakebase (05) and either the Serving endpoint path (06) or the separate Agent App proxy path (06d). 08-appkit-feedback requires 07-appkit-chat-history (it reads the Vote table and traceId column that 07 creates).

Step	Skill / Prompt	What It Does
Scaffold, Build & Test	01-appkit-scaffold + 02-appkit-build	Scaffold a blank AppKit project, build UI with mock data from PRD
Deploy to Databricks Apps	03-appkit-deploy	Deploy mock-data app to Databricks Apps
Setup Lakebase	04-appkit-plugin-add + apps_lakebase/prompts/03-setup-lakebase.md	Install Lakebase plugin and configure bundle resources in databricks.yml
Wire Lakebase Backend	04-appkit-plugin-add + 05-appkit-lakebase-wiring + apps_lakebase/prompts/04-lakebase-wiring.md	Add Lakebase plugin, design schema, build APIs, wire frontend — code changes only, does NOT deploy
Wire Agent Endpoint	04-appkit-plugin-add + 06-appkit-serving-wiring	Install Serving plugin, wire agent endpoint to frontend — code changes only, does NOT deploy
Wire Separate Agent App	06d-appkit-agent-app-proxy	Connect AppKit frontend to a separate Agent App backend with OBO forwarding and /api/chat SSE
Persist Chat History	04-appkit-plugin-add + 05-appkit-lakebase-wiring + (06-appkit-serving-wiring or 06d-appkit-agent-app-proxy) + 07-appkit-chat-history	Add chat schema, session auth, sidebar, stream+persist proxy, ephemeral mode
Add User Feedback	07-appkit-chat-history + 08-appkit-feedback	Add thumbs up/down linked to MLflow assessments (AppKit-native auth)
Deploy and E2E Test	03-appkit-deploy + apps_lakebase/prompts/05-e2e-test.md	Deploy with Lakebase/Serving (SP creates DB objects) + E2E test

Start at Scaffold, Build & Test for new projects. Jump to any step if prior steps are complete.

Lakebase flow: After Wire Lakebase Backend, the app has Lakebase code but runs locally with mock fallback data. Deploy and E2E Test deploys so the Service Principal creates database objects, then runs E2E verification.

Skill-driven vs prompt-driven steps: Scaffold/Build and Wire Lakebase Backend are skill-driven — the prompt delegates to skills for reusable patterns. Setup Lakebase and Deploy and E2E Test are prompt-driven — the prompt contains application-specific procedures with skills as supplementary references. Skills encode reusable, PRD-independent knowledge (how to scaffold, deploy, register a plugin, wire a database). Prompts encode orchestration and application-specific context (variable values, step prerequisites, handoff instructions).

---

Task Routing Table

Match the user's request keywords to the correct skill. Read the skill's SKILL.md before proceeding.

Keywords	Route To	Purpose
"create app", "scaffold", "init", "new app", "bootstrap", "start new project"	apps_lakebase/skills/01-appkit-scaffold/SKILL.md	Create a new AppKit project
"add plugin", "add lakebase", "add analytics", "add genie", "add files", "integrate postgres", "extend app"	apps_lakebase/skills/04-appkit-plugin-add/SKILL.md	Add a plugin to an existing project
"build UI", "implement PRD", "create dashboard", "add page", "build features", "develop frontend", "create components"	apps_lakebase/skills/02-appkit-build/SKILL.md	Build features from a PRD or spec
"setup lakebase", "add lakebase plugin", "lakebase bundle resources", "configure lakebase"	apps_lakebase/skills/04-appkit-plugin-add/SKILL.md + apps_lakebase/prompts/03-setup-lakebase.md	Install Lakebase plugin, declare bundle resources
"wire lakebase", "connect lakebase", "lakebase wiring", "lakebase backend", "CRUD API", "lakebase tables", "DDL"	apps_lakebase/skills/05-appkit-lakebase-wiring/SKILL.md (patterns) + apps_lakebase/prompts/04-lakebase-wiring.md (orchestration)	Wire Lakebase to UI — code changes only, does NOT deploy
"database schema design", "useLakebaseData", "ConnectionStatus", "mock fallback", "database design"	apps_lakebase/skills/05-appkit-lakebase-wiring/SKILL.md	Lakebase wiring patterns (DDL, API routes, frontend hooks, testing)
"e2e test", "test lakebase", "deploy lakebase", "verify live data"	apps_lakebase/Instructions.md Deploy and E2E Test step or apps_lakebase/prompts/05-e2e-test.md	Deploy with Lakebase (SP creates DB objects), test APIs, verify idle resilience
"lakebase CLI", "lakebase troubleshoot", "lakebase branches", "lakebase roles"	databricks-lakebase agent skill (installed via Databricks Agent Skills). Fallback: https://github.com/databricks/databricks-agent-skills/blob/main/skills/databricks-lakebase/SKILL.md	Advanced Lakebase CLI operations, troubleshooting, branches, roles
"wire agent", "agent endpoint", "serving plugin", "agent UI", "chat interface", "model serving", "useServingStream", "serving wiring"	apps_lakebase/skills/06-appkit-serving-wiring/SKILL.md	Wire a Model Serving / Agent endpoint to the AppKit frontend
"agent app backend", "two apps", "separate Agent App", "appkit plus agent app", "agent app proxy", "OBO forwarding", "x-forwarded-access-token"	apps_lakebase/skills/06d-appkit-agent-app-proxy/SKILL.md	Wire AppKit to a separate Agent App with app-to-app auth and end-user OBO forwarding
"chat history", "save conversations", "persistent chat", "conversation sidebar", "message storage", "save messages", "ephemeral chat"	apps_lakebase/skills/07-appkit-chat-history/SKILL.md	Persist agent chat conversations to Lakebase with session auth + sidebar
"feedback", "thumbs up", "thumbs down", "rate response", "MLflow assessment", "user rating", "vote on message"	apps_lakebase/skills/08-appkit-feedback/SKILL.md	Add user feedback linked to MLflow assessments (AppKit-native auth)
"deploy", "push to production", "ship app", "fix deploy error", "app won't start", "redeploy"	apps_lakebase/skills/03-appkit-deploy/SKILL.md	Deploy to Databricks Apps

---

Routing Algorithm

1. User request received
2. Detect keywords from the routing table above
3. IF "create" / "new" / "scaffold" / "init"         → Read apps_lakebase/skills/01-appkit-scaffold/SKILL.md
4. IF "add plugin" / "integrate" / "add lakebase"     → Read apps_lakebase/skills/04-appkit-plugin-add/SKILL.md
5. IF "build" / "implement" / "PRD" / "UI"            → Read apps_lakebase/skills/02-appkit-build/SKILL.md
6. IF "setup lakebase" / "add lakebase plugin"         → Read apps_lakebase/skills/04-appkit-plugin-add/SKILL.md (plugin install)
                                                        + apps_lakebase/prompts/03-setup-lakebase.md (bundle resources)
7. IF "wire lakebase" / "connect lakebase" / "DDL"   → Read apps_lakebase/skills/05-appkit-lakebase-wiring/SKILL.md (patterns)
                                                        + apps_lakebase/prompts/04-lakebase-wiring.md (orchestration, no deploy)
8. IF "wire agent" / "serving plugin" / "agent endpoint" / "model serving"
                                                      → Read apps_lakebase/skills/06-appkit-serving-wiring/SKILL.md
9. IF "agent app proxy" / "two apps" / "separate Agent App" / "OBO forwarding"
                                                      → Read apps_lakebase/skills/06d-appkit-agent-app-proxy/SKILL.md
10. IF "chat history" / "save conversations" / "persistent chat" / "conversation sidebar"
                                                      → Read apps_lakebase/skills/07-appkit-chat-history/SKILL.md
11. IF "feedback" / "thumbs" / "MLflow assessment" / "rate response" / "user rating"
                                                      → Read apps_lakebase/skills/08-appkit-feedback/SKILL.md
12. IF "e2e test" / "test lakebase" / "deploy lakebase" → Read apps_lakebase/prompts/05-e2e-test.md (deploy + E2E)
13. IF "lakebase CLI" / "lakebase troubleshoot"       → Read and follow databricks-lakebase agent skill
14. IF "deploy" / "ship" / "fix deploy"               → Read apps_lakebase/skills/03-appkit-deploy/SKILL.md
15. IF ambiguous or multi-step                        → Ask user to clarify, or follow
                                                        the lifecycle order (scaffold → build → deploy)

---

Skill Inventory

Skill	Path	Role	Standalone	Upstream Sources
01-appkit-scaffold	apps_lakebase/skills/01-appkit-scaffold/	scaffold	yes	AppKit docs, databricks-agent-skills
04-appkit-plugin-add	apps_lakebase/skills/04-appkit-plugin-add/	plugin-integration	yes	AppKit plugin docs
02-appkit-build	apps_lakebase/skills/02-appkit-build/	build	no (needs scaffold)	AppKit docs, Anthropic frontend-design
03-appkit-deploy	apps_lakebase/skills/03-appkit-deploy/	deploy	yes	App management, Configuration
05-appkit-lakebase-wiring	apps_lakebase/skills/05-appkit-lakebase-wiring/	lakebase-wiring	no (needs plugin-add)	Lakebase plugin docs
06-appkit-serving-wiring	apps_lakebase/skills/06-appkit-serving-wiring/	serving-wiring	no (needs plugin-add)	Serving plugin docs
06d-appkit-agent-app-proxy	apps_lakebase/skills/06d-appkit-agent-app-proxy/	agent-app-proxy	no (needs deployed Agent App)	Databricks agent apps docs, AppKit server docs
07-appkit-chat-history	apps_lakebase/skills/07-appkit-chat-history/	chat-history	no (needs 05 + 06 or 06d)	Lakebase plugin docs, Serving plugin docs
08-appkit-feedback	apps_lakebase/skills/08-appkit-feedback/	feedback	no (needs 07)	Serving plugin docs, MLflow Traces API

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To see the full directory tree, run: find apps_lakebase/skills/ -type f -name "*.md" | sort

Skill Dependencies