Use when integrating with an API endpoint and need TypeScript types, contracts, and adapters generated automatically.

Use when training Roboflow models, diagnosing why a model underperforms, improving accuracy, or setting up a production feedback loop — covers architecture selection, model IDs, checkpoints, Model Evaluation (confusion matrix, per-class metrics, MCP eval tools), the diagnosis-first improvement playbook, and Active Learning through the Project Model Workflow block.

Use this skill when adding and configuring the RevenueCat Android SDK (purchases-android, artifact com.revenuecat.purchases:purchases) in an app. Covers the Gradle dependency, Purchases.configure with PurchasesConfiguration, initial app user id strategy, and log level.

KB article quality reviewer. Run against KB articles in docs/kb/ to review frontmatter, article type and structure, title format, product names, callout format, bolding/path formatting, image alt-text/external-references, and keyword quality. Use when editing or reviewing any file under docs/kb/.

Create, configure, and manage Netlify deploys from code — reach for this when setting up Git continuous deployment, running netlify deploy or netlify deploy --prod from the CLI, writing netlify.toml deploy contexts, adding a Deploy to Netlify button, wiring build hooks, configuring Deploy Previews or branch deploys, locking or skipping deploys, fixing a failed or secrets-scanning deploy, or when someone asks to "deploy my site", "set up preview deploys", "add per-branch build config", "keep staging out of Google", or "add a deploy button to my README".

Use when querying or calling pay-per-token foundation models, or when creating, updating, listing, or querying Unity Gateway (also called Unity AI Gateway) services, including model provider services, MCP services, system.ai services, and three-part Unity Catalog service names (catalog.schema.service). Also use for managing spend budgets and usage alerts on Unity Gateway, and for migrating from legacy AI Gateway. Also use when a workload with Model Serving endpoint permissions (for example CAN_QUERY) gets PERMISSION_DENIED querying a three-part model name, since serving-endpoint access does not grant access to a Unity Gateway service. Not for configuring legacy AI Gateway on Model Serving endpoints; use databricks-model-serving for that.

Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); no-code document / data agents incl. legacy Knowledge Assistants & Supervisor Agents (databricks-genie-agents); MLflow evaluation (databricks-mlflow-evaluation).

Databricks Lakebase Postgres: projects, scaling, connectivity, Lakebase synced tables, and Data API. Use when asked about Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks.

Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.

Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.

Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.

Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.

Build and troubleshoot Cloudflare K2 or K2 Streams durable logs. Use for stream setup, producing from Workers or HTTP, configuring retention and inputs, and consuming through subscriptions.

Use when writing, modifying, or debugging unit tests (*.test.tsx) in the orchestration cluster webapp (webapp/client/apps/orchestration-cluster-webapp/src/). Covers Vitest browser mode, MSW mocking, and vitest-browser-react rendering.

Conduct proactive, hypothesis-driven threat hunts — search SIEM / EDR / logs for adversaries who haven't tripped an alert yet. ATT&CK-driven, hypothesis-based methodology. Use when the user mentions 'threat hunting,' 'proactive hunt,' 'TaHiTI,' 'PEAK framework,' 'MITRE ATT&CK hunt,' 'hypothesis-driven hunt,' 'hunt hypothesis,' 'living off the land,' 'LOLBins,' 'beaconing,' 'lateral movement detection,' 'data staging,' 'persistence hunting,' or wants to find threats that have evaded existing detections.

Audit project dependencies, frameworks, languages, and dev tools for known vulnerabilities, CVEs, and security anti-patterns. Use when the user mentions 'dependency audit,' 'npm audit,' 'CVE,' 'vulnerable packages,' 'supply chain security,' 'outdated dependencies,' 'known vulnerabilities,' 'security advisory,' 'package security,' 'framework vulnerability,' 'is this package safe,' 'pnpm audit,' 'yarn audit,' 'bundle audit,' 'patch this CVE,' 'audit fix broke,' 'lockfile diff,' 'dependency confusion,' 'registry redirection,' 'MCP server pinning,' 'release pipeline,' or needs to check whether their stack, CI, or release pipeline has known security issues.

S3-compatible object storage that branches with your Neon project, so files and the database stay in sync across every branch. Use when a user wants object storage, a bucket, blob/file storage, or somewhere to put uploads, images, documents, avatars, or user-generated files for their app or agent — especially when they already use (or are setting up) Lakebase Postgres and don't want to add a separate storage provider like AWS S3, Cloudflare R2, or Supabase Storage. Triggers include "object storage", "bucket", "blob storage", "file storage", "store uploads/images/files", "S3-compatible storage", "presigned URL", "where do I put files", "storage logs", "bucket logs", "CDN in front of object storage", "Neon Object Storage", "Neon Storage", and "storage that branches with my database".

Measuring and optimizing three.js speed: render statistics, memory counters, fewer draw calls via merging, instancing, batching and LOD, fill rate, shadows, CPU work per frame, shader stalls and GPU compute for particles, WebGL or WebGPU with TSL. Use when a scene is slow, janks or exceeds memory.

This skill is required to create, read, edit, review, or comment on Figma specs. You must read it when working on a PRD, brief, RFC or any kind of document in either a standalone Figma spec or a Figma spec embedded in a Figma Design or Figjam file.

Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for /arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.