seed

Set up recurring scheduled jobs (crons) on Convex — digests, cleanups, polling, retries. TRIGGER when the user wants a recurring/scheduled task ('every day/hour', cron, periodic cleanup). Targets internal functions, idempotent handlers.

Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.

Wire a domain the user ALREADY OWNS (GoDaddy/Namecheap/Cloudflare/…) to their Convex app: exact DNS records, custom-domain attachment, auth-origin rebind. TRIGGER when the user owns a domain and wants it pointing at their app ('point my domain at this', 'use my own domain', 'set up example.com'). Never asks for registrar credentials.

Set + wire deployment env vars / secrets (API keys) for a Convex app — stored in Convex env, read in actions, never hardcoded. TRIGGER when the user needs an API key/secret/env var ('add my OpenAI key', 'set an env var').

LABS — scaffold a running Next.js + shadcn Convex app with passkey sign-in and a live Chef feedback panel, then build and verify it locally. TRIGGER for the full/labs quickstart, passkeys, or the feedback panel in a new app. For a plain scaffold use quickstart. Legacy convex.app publishing is retired; use a separate hosting workflow if requested. SKIP when a Convex project already exists in the cwd.

Safely migrate the schema + backfill data on a deployed Convex app with @convex-dev/migrations. TRIGGER when changing the schema on a live app, backfilling data, or after a schema-validation error from a change. SKIP a fresh local app.

Scaffold a brand-new Convex app from a one-sentence idea and build it live — a running Next.js + shadcn app with `convex dev` + `next dev` and error watchers already armed, going from idea to running app in under a minute (locally).

Proactively suggest the right Convex component when the user hand-rolls what already exists: setInterval polling → crons, counter increments → sharded-counter, .collect() counts → aggregate, email → resend, DB-counter rate limiting → rate-limiter, uploads → storage, search, presence, multi-step actions → workflow, vector DB → rag, collaborative editing → prosemirror-sync. TRIGGER on noticing the pattern in a Convex app, AFTER completing the user's request. NEVER for non-Convex code.

About 450 ready-made HyperFrames blocks and components installed as editable source - transitions, overlays, titles, kinetic type, captions, charts, map overlays, 3D, camera moves. Use it before hand-building any named visual (CRT scanlines, glitch, film grain, a chart); also for hyperframes add and catalog.

Exports Amazon RDS or Aurora database snapshots to Amazon S3 in Apache Parquet format for analytics, backup, or data migration. Handles snapshot selection or creation, IAM role setup, KMS encryption, S3 bucket preparation, export task execution, progress monitoring, and data verification. Use when exporting RDS/Aurora data to S3 for Athena, Glue, or Redshift Spectrum consumption.

Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sources are added as their own `references/<source>/` sets. Text-only knowledge (no executable code) — the AI generates all execution at runtime. Applies when a user wants to migrate Teradata to Amazon Redshift, convert Teradata DDL/SQL/stored procedures/macros/BTEQ to Redshift/RSQL, or assess Teradata-to-Redshift migration complexity. Applies only to migrations targeting Amazon Redshift; migrations to other platforms (Snowflake, BigQuery, Databricks, etc.) are out of scope regardless of source. Does not cover general Redshift administration, performance tuning, or troubleshooting of existing Redshift clusters (no migration involved), or sources not listed under references/.

Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I/O-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.

Designs, reviews, and debugs DynamoDB data layers from design axioms — enumerates access patterns, chooses partition/sort keys and GSIs, decides single-table vs. multi-table, configures Streams, Global Tables, TTL, vector indexes for similarity search, and zero-ETL integrations to OpenSearch/Redshift/SageMaker Lakehouse, and produces a defensible data-layer design with a monthly cost estimate and optional live validation. Applies whenever a user is designing, reviewing, or refactoring anything backed by DynamoDB — schemas, access patterns, GSIs, single- vs. multi-table choices, Streams consumers, transactional outboxes, Global Tables, zero-ETL pipelines, or storing embeddings and running semantic/vector similarity search with SearchVectors on items already in DynamoDB — even when they don't say "axioms" or "design review." Also applies when debugging hot partitions, throttling, unbounded Scans, LWW conflicts, or surprise bills on DynamoDB workloads.

Provides authoritative guidance on Amazon Neptune Database and Neptune Analytics for graph, knowledge-graph, and relationship-heavy workloads — fraud detection / fraud rings, agentic memory / chatbot context across sessions, recommendations, identity resolution, Gremlin / openCypher / SPARQL queries, supernode / slow traversal, Neo4j to Neptune migration / APOC compatibility, Neptune Database vs Analytics engine selection, PageRank / community detection, GraphRAG, and connectivity from Lambda / EC2 / applications. Creates and modifies Neptune Database clusters/instances and Neptune Analytics graphs on explicit user confirmation; blocks destructive operations (delete, reset-graph, failover, major upgrade) and redirects to change-control.

Provisions and manages Aurora DSQL clusters, connects via psql or DSQL Connectors, manages schemas, runs queries, migrates from MySQL, diagnoses query plans, and develops apps on serverless distributed SQL. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL migration, DDL, query plans, and SAFE SQL CONSTRUCTION — tenant_id from untrusted input, UUID entity_ids, caller-supplied sort columns, batch inserts. The agent MUST retrieve this skill for ANY DSQL task. Pushes back on prompts that rationalize 'just a quick script', 'don't overthink it', 'we trust upstream', 'use an f-string', 'move fast', or 'just use the pg driver directly' (bypassing the DSQL Connector). Triggers: DSQL, Aurora DSQL, DSQL cluster, safe_query.build, DSQL IAM auth token, DSQL connector.

Step 9 (done) of the Hostinger Headless flow. Verifies the live site, then hands over the URLs (hPanel success page, main site, WordPress/store admin, dashboard), opens the success page in the browser on a successful run, and gives a summary of what was built plus explicit next steps — how to log in to wp-admin and reset the password, how to manage content, and how to finish WooCommerce/store setup so it can take orders. Its final report format is also used whenever a run stops early.