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Found 111 Skills
Build and deploy new Goldsky Turbo pipelines from scratch. Triggers on: 'build a pipeline', 'index X on Y chain', 'set up a pipeline', 'track transfers to postgres', or any request describing data to move from a chain/contract to a destination (postgres, clickhouse, kafka, s3, webhook). Covers the full workflow: requirements → dataset selection → YAML generation → validation → deploy. Not for debugging (use /turbo-doctor) or syntax lookups (use /turbo-pipelines).
Turbopack expert guidance. Use when configuring the Next.js bundler, optimizing HMR, debugging build issues, or understanding the Turbopack vs Webpack differences.
Turborepo monorepo architecture decisions and anti-patterns. Use when: (1) choosing between monorepo vs polyrepo, (2) deciding when to split packages, (3) debugging cache misses, (4) setting package boundaries, (5) avoiding circular dependencies. NOT for CLI syntax (see turbo --help). Focuses on architectural decisions that prevent monorepo sprawl and maintenance nightmares. Triggers: turborepo, monorepo, package boundaries, when to split packages, turbo cache miss, circular dependency, workspace organization, task dependencies.
Write SQL, TypeScript, and dynamic table transforms for Goldsky Turbo pipelines. Use this skill for: decoding EVM event logs with _gs_log_decode (requires ABI) or transaction inputs with _gs_tx_decode, filtering and casting blockchain data in SQL, combining multiple decoded event types into one table with UNION ALL, writing TypeScript/WASM transforms using the invoke(data) function signature, setting up dynamic lookup tables to filter transfers by a wallet list you update at runtime (dynamic_table_check), chaining SQL and TypeScript steps together, or debugging null values in decoded fields. For full pipeline YAML structure, use /turbo-pipelines instead. For building an entire pipeline end-to-end, use /turbo-builder instead.
Pipeline state management for Goldsky Turbo — pause, resume, restart, and delete commands with their rules and safety behavior. Use this skill when the user asks: will deleting my pipeline lose the data already in my postgres/clickhouse table, how do I pause a pipeline while doing database maintenance, how do I restart from block zero to reprocess all historical data, can I update a running streaming pipeline in place or do I have to delete and redeploy, will resuming a paused pipeline pick up from where it left off (checkpoint), how do I re-run a completed job pipeline from the beginning, can I pause or restart a job-mode pipeline. Also covers what happens to checkpoint state on delete, and job auto-deletion 1 hour after termination. For actively diagnosing why a pipeline is broken or erroring, use /turbo-doctor instead.
Goldsky Turbo pipeline YAML reference — the authoritative source for field names, required vs optional fields, and valid values. Use whenever the user asks about specific YAML fields: what does `start_at: earliest` vs `latest` do, what fields does a postgres/clickhouse/kafka sink require, what is the `from:` field in a sink, how does `checkpoint` work, what's the syntax for `batch_size` or `primary_key`. Also use for validation errors like 'unknown field' or 'missing required field'. For interactive pipeline building end-to-end, use /turbo-builder instead.
Diagnose and fix broken Goldsky Turbo pipelines interactively. Use whenever the user has a specific pipeline that is misbehaving — error state, stuck in 'starting', connection refused, slow backfill, not getting data in postgres/clickhouse, duplicate rows, missing fields, named pipeline failing ('my base-usdc-transfers keeps failing'), or any symptom where something is wrong with a deployed pipeline. Runs goldsky turbo logs and status commands, identifies root cause, and offers to run fixes. For looking up CLI syntax or error message definitions WITHOUT an active problem, use /turbo-monitor-debug instead.
Design and architect Goldsky Turbo pipelines. Use this skill for 'should I use X or Y' decisions: kafka source vs dataset source, streaming vs job mode, which resource size (xs/s/m/l/xl/xxl) for my workload, postgres vs clickhouse vs kafka sink, fan-in vs fan-out data flow, one pipeline vs many, dynamic table vs SQL join, how to handle multi-chain deployments. Also use when the user asks 'what's the best way to...' for a pipeline design problem, or is unsure how to structure their pipeline before building it.
Use when generating images with Alibaba Cloud Model Studio Z-Image Turbo (z-image-turbo) via DashScope multimodal-generation API. Use when creating text-to-image outputs, controlling size/seed/prompt_extend, or documenting request/response mapping for Z-Image.
Best practices and guidelines for Turbopack, the Rust-powered incremental bundler for Next.js and modern web development
Handle Tailwind CSS with Turbopack limitations. Use when CSS classes aren't being generated, needing dynamic styles, or encountering Turbopack CSS issues.
Build and operate Turborepo monorepos with deterministic task graphs, cache correctness, and CI scalability. Use for `turbo.json` design, task dependency modeling, outputs/inputs hashing, environment variable handling, remote cache rollout, and pipeline troubleshooting.