Menu

Individual skill

ohlcv-processing

0upvotes

Market data preparation including OHLCV resampling, gap handling, anomaly detection, normalization, and multi-source merging

skills/ohlcv-processing/SKILL.md

Read pinned source

Source commit 981e1d736cdc02bdc1c55c74ec9224e956414706

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 10, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
521
Repository last updated
Sep 3, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

  • data Derived category

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# OHLCV Processing — Market Data Preparation

Clean, consistent OHLCV data is the foundation of every trading analysis. Garbage in, garbage out — a single anomalous candle can trigger false signals, corrupt indicator calculations, and produce misleading backtest results. This skill covers the full data preparation pipeline: validation, cleaning, resampling, normalization, and multi-source merging.

**Why this matters**: Crypto OHLCV data is messier than traditional markets. 24/7 trading means no official close, DEX aggregators disagree on prices, low-liquidity tokens produce impossible candles, and API outages create gaps. Every analysis workflow should start with this pipeline.

## Quick Start

### 1. Install Dependencies

```bash
uv pip install pandas numpy httpx
```
Back to top