sendaifun/solana-new/build-data-pipeline
Claude Code and agent skill by sendaifun/solana-new
- community
Checking that the SKILL.md file is still in the repository.
Guide a developer through building a Solana data pipeline or indexer. Use when a user says "build an indexer", "data pipeline", "analytics", "track transactions", "monitor wallets", "webhook", "index accounts", or "real-time data". Reads build-context.md from a prior scaffold phase if available.
Install
npx vskill@latest install sendaifun/solana-new/build-data-pipelineSKILL.md
Preamble (run first)
If TEL_PROMPTED is no: Before starting the skill workflow, ask the user about telemetry. Use AskUserQuestion:
Help superstack get better! We track which skills get used and how long they take —no code, no file paths, no PII. Change anytime in~/.superstack/config.json.
Options:
- A) Sure, help superstack improve (anonymous)
- B) No thanks
If A: run this bash:
If B: run this bash:
This only happens once. If TEL_PROMPTED is yes, skip this entirely and proceed to the skill workflow.
Wrong skill? See SKILL_ROUTER.md for all available skills.
Build Data Pipeline
Overview
Guide the user through building a data pipeline that ingests, transforms, and stores Solana on-chain data. Covers real-time event streaming via webhooks and WebSockets, historical backfilling, account state indexing, and building query-friendly storage. Uses Helius where it is the best fit for production-grade ingestion, while keeping the storage and indexing design provider-agnostic.
Workflow
- Check for
.superstack/build-context.md. If found, use stack decisions. If not, ask: what data do you need (transactions, account state, token transfers, program events)? Real-time, historical, or both? Write.superstack/build-context.mdwith the context gathered so future skills can use it. - Read references/indexing-patterns.md to select the right ingestion method.
- Read references/data-storage.md to design the storage schema.
- Implement in milestones:
a. Set up data ingestion (Helius webhook, WebSocket subscription, or geyser plugin) b. Build the parser/transformer for your specific data format c. Design and create the database schema d. Implement write path (ingestion → parse → store) e. Build query API or dashboard on top of stored data
- Test with live devnet data, then switch to mainnet when ready.
- Monitor ingestion lag and handle missed events with backfill logic.
Non-Negotiables
- Always implement idempotent writes — webhooks and WebSockets can deliver duplicates.
- Include a backfill mechanism — you will miss events during deploys, restarts, and outages.
- Never store raw transaction blobs without parsing — they are expensive to query later.
- Use Helius enhanced transactions for parsed data instead of raw RPC when possible.
- Monitor ingestion lag — if your pipeline falls behind, you need alerts, not silent data loss.
- Store the slot number with every record for ordering and deduplication.
Phase Handoff
This skill is Phase 2 (Build) in the Idea → Build → Launch journey.
Reads: .superstack/build-context.md Writes/Updates: .superstack/build-context.md (creates if missing) with:
pipeline.ingestion_method: "webhook" | "websocket" | "geyser" | "rpc-polling"pipeline.data_types: string[] (e.g., ["transactions", "account-state", "token-transfers"])pipeline.storage: "postgresql" | "redis" | "custom"pipeline.backfill_implemented: boolean
When updating, deep-merge — don't overwrite existing fields.
See ../../data/specs/phase-handoff.md for the full JSON contract.
Quick Start
Decision Points
- Which ingestion method? Webhooks (simplest, Helius) → WebSocket (real-time) → Geyser (highest throughput) → Polling (last resort).
- Which RPC? Helius is required if you want Helius webhooks or Helius-only enhanced APIs. DAS is available from multiple providers (for example Helius, MetaMask/Infura, and QuickNode), so choose based on pricing, limits, and where the rest of your stack already lives.
- Database? PostgreSQL for relational data + transactions. Redis for caching + real-time state. SQLite for small/local indexers.
- Hosting? Railway or Fly.io for webhook receivers. AWS/GCP for Geyser plugins.
Resources
references/
Telemetry (run last)
After the skill workflow completes (success, error, or abort), log the telemetry event. Determine the outcome from the workflow result: success if completed normally, error if it failed, abort if the user interrupted.
Run this bash:
Replace OUTCOME with success/error/abort based on the workflow result.
Security
- Security scanPassed, 96 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/build/build-data-pipeline/SKILL.md
Popularity
- Repository stars
- 144
- Repository forks
- 40
- 7-day trend score
- 25
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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