tezos_data_to_supabase_pipeline

Ingest Tezos indexer data into Supabase with idempotent upserts and resumable checkpoints.

2|Updated Apr 13, 2026
One-click install
npx skills add https://github.com/Paulwhoisaghostnet/kiln --skill tezos-data-to-supabase-pipeline
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tezos_data_to_supabase_pipeline
Source: https://github.com/Paulwhoisaghostnet/kiln/tree/main/skllz/skills/tezos_data_to_supabase_pipeline
Command: npx skills add https://github.com/Paulwhoisaghostnet/kiln --skill tezos-data-to-supabase-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Ingest Tezos indexer data into Supabase with idempotent upserts and resumable checkpoints.

Core Features & Use Cases

  • End-to-end ingestion of Tezos blockchain/indexer data into Supabase with durable checkpoints.
  • Idempotent upserts and bounded replay to support replay-safe analytics and verification queries.
  • Reference-informed workflow leveraging checkpointing to enable resumable, fault-tolerant pipelines.

Quick Start

Define bounded data scope (entities, network, lookback window, filters); create/verify Supabase schema and unique keys; resume from the sync_state checkpoint; ingest with cursor pagination (offset.cr) and bounded retries; upsert idempotently and advance checkpoint only after successful writes; run verification queries and publish sync report.

Frequently Asked Questions about tezos_data_to_supabase_pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ingest Tezos indexer data into Supabase with idempotent upserts?▼

Tezos data ingestion uses resumable checkpoints to ensure fault tolerance by advancing the sync_state checkpoint only after successful idempotent upserts, preventing duplicate records during replays.

What is the best way to resume a Tezos data pipeline after a failure?▼

The best way to resume a Tezos data pipeline after failure is to resume from the last sync_state checkpoint, using cursor pagination and bounded retries to continue ingestion without data duplication.

Does this Tezos ingestion workflow support TZKT and Objkt indexer feeds?▼

Yes, this Tezos ingestion workflow supports TZKT and Objkt indexer feeds, applying bounded windows and cursor pagination to verify and ingest data across various Tezos networks.

Can I use bounded replay for replay-safe analytics when ingesting Tezos blockchain data?▼

Yes, you can use bounded replay for replay-safe analytics because the ingestion pipeline applies idempotent upserts to ensure that reprocessing historical Tezos blockchain data yields consistent results.

How do I verify Tezos data pipelines after ingesting indexer records into Supabase?▼

You verify Tezos data pipelines by running verification queries against the ingested Supabase records, then publishing a structured sync report to monitor pipeline health and bounded window completion.