Finder of Truth
A privacy-first blockchain inspection toolkit powered by Find Labs API.
Videos
Description
Finder of Truth (FoT)
A privacy-first blockchain inspection toolkit powered by Find Labs API.
Overview
Finder of Truth (FoT) is a lightweight, local-first developer toolkit for the Flow Testnet that connects directly to a Flow wallet, fetches verified account data from Find Labs, Flowscan, and Flow REST, and stores local snapshots for transparent, auditable blockchain analysis.
It enables developers, auditors, and researchers to perform fast, structured, and private inspections of any Flow account — all from the browser, with no backend required.
Key Features
Wallet Integration
Connect to a Flow Testnet wallet using @onflow/fcl.
Instantly view account metadata and balances.
Automatic cleanup and isolation for each wallet’s local snapshots.
Account Data Extraction
Find Labs API: structured data for tokens, NFTs, transactions, and contracts.
Flow REST: account state, balances, and key metadata.
Flowscan HTML parsing: extra UI fields such as storage, staked, and delegated amounts.
Tab-by-tab extraction: transactions, keys, tokens, collections, and events.
Change detection system: snapshots are saved only when new data differs from previous records.
Local Persistence and Privacy
All data is stored in-browser (
localStorage) underfindtruth_snapshots_v1_<WALLET_ADDR>.Each snapshot includes:
Find Labs API data
Flow REST responses
Parsed Flowscan context
Configurable snapshot retention and size limits.
Developer UX
100% frontend — no backend setup required.
Dev-time proxy for CORS-free API calls.
Minimal, focused UI in cream / orange / black tones.
Integrated snapshot viewer (sortable and filterable).
Export and Analytics
Export snapshots as JSON for downstream analysis or ingestion into:
Dune Analytics
MongoDB / Postgres / Supabase
Custom data pipelines
JSON structure designed for easy queryability and reproducibility.
Technical Stack
Frontend: React, Vite, TypeScript
Styling: TailwindCSS (custom orange–cream–black theme)
Wallet Integration: @onflow/fcl (Flow Testnet)
APIs: Find Labs, Flow REST, Flowscan
Storage: LocalStorage (privacy-first persistence)
Development Tools: Vite proxy, DOMParser, async batch requests
Integration with Analytics Tools
Finder of Truth exports verifiable, structured data that can easily be used in external analytics systems.
Typical Workflow
Run a local snapshot → export JSON
Upload JSON to shared storage or database
Use Dune, BigQuery, or any SQL-based system for analysis and visualization
Examples:
Tracking token balance evolution
Auditing NFT transactions
Analyzing key rotation and activity patterns
Target Users
Developers building and testing Flow-native applications
Auditors performing on-chain account verifications
Researchers analyzing transaction and ownership patterns
Roadmap
Phase | Feature | Status |
|---|---|---|
Core Connect | Wallet + Find Labs + REST integration | ✅ |
Local Snapshots | Per-wallet persistence | ✅ |
Snapshot Diffing | Detect and store meaningful changes | 🏗️ |
Snapshot Viewer | In-app browsing of saved data | 🏗️ |
Export Tool | JSON export/import | ⏳ |
Server Mode | Optional persistence for teams | 🔜 |
Data Schema | Standardized structured objects | 🔜 |
Why This Approach Works
Privacy-first — all snapshots remain local unless explicitly exported.
Verifiable — every snapshot includes raw API data for audit reproducibility.
Fast and developer-oriented — runs entirely in the browser, no setup friction.
Extensible — can evolve into a server-backed analytics engine when needed.
Call to Action
Connect your Flow Testnet wallet, capture an account snapshot using Find Labs, and explore the verified on-chain state instantly — privately, locally, and audibly.
Finder of Truth — discover, verify, and own your blockchain insights.
Progress During Hackathon
Progress Wallet connection and Find Labs integration are complete (100%). Local snapshotting and Flow REST merging are nearly finished (90%). UI for snapshot viewing and export is in progress (60%). Server persistence and structured parsing are upcoming (30%).