tradedesk-miner

Mine statistical candidates from cached OHLCV data into NDJSON envelopes.

Updated Apr 3, 2026
One-click install
npx skills add https://github.com/radiusred/skills --skill tradedesk-miner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tradedesk-miner
Source: https://github.com/radiusred/skills/tree/main/tradedesk-miner
Command: npx skills add https://github.com/radiusred/skills --skill tradedesk-miner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The tradedesk-miner CLI enables analysts to mine raw statistical candidates from cached OHLCV data, emitting findings as a stream of NDJSON envelopes for downstream hypothesis testing.

Core Features & Use Cases

  • High-performance data-mining engine for historical OHLCV data.
  • Supports targeted single-scan execution (miner scan) and broad discovery sweeps (miner sweep) across instruments, timeframes, and windows.
  • Produces deterministic NDJSON findings with a reproducible provenance footprint for byte-identical re-runs.

Quick Start

Run the miner against a prepared OHLCV cache to emit findings to stdout.

Frequently Asked Questions about tradedesk-miner

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

FAQPage Schema
How do I mine OHLCV data for hypothesis testing?▼

To mine OHLCV data for hypothesis testing, run targeted single-instrument scans or multi-instrument sweeps to produce NDJSON findings with provenance metadata for reproducible discovery.

What is NDJSON format used for in financial data mining?▼

In financial data mining, NDJSON format is used to stream deterministic findings envelopes from cached OHLCV data, ensuring byte-identical re-runs for downstream hypothesis testing.

How do I ensure reproducibility when scanning historical OHLCV data?▼

Ensure reproducibility when scanning historical OHLCV data by configuring cache-root and output-path, which attaches per-run provenance metadata like param_hash and code_revision to the output.

Can I run multi-instrument sweeps across different timeframes?▼

Yes, you can run multi-instrument sweeps across different timeframes and windows to facilitate broad statistical discovery from cached OHLCV data.

Does the miner require a pre-configured OHLCV cache?▼

Yes, the miner requires a prepared OHLCV cache to execute high-performance data-mining scans and emit statistical candidates directly to stdout.

What is the best way to handle raw statistical candidate discovery?▼

The best way to handle raw statistical candidate discovery is using a dedicated mining engine to emit deterministic NDJSON envelopes, ensuring reproducible provenance footprints for downstream analysis.