channel-name-parsing

Parse CHANNELNAMES.txt files to map cycle numbers to channel name lists.

3|Updated Dec 10, 2025
One-click install
npx skills add https://github.com/smith6jt-cop/Skills_Registry --skill channel-name-parsing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: channel-name-parsing
Source: https://github.com/smith6jt-cop/Skills_Registry/tree/main/plugins/kintsugi/channel-name-parsing/skills/channel-name-parsing
Command: npx skills add https://github.com/smith6jt-cop/Skills_Registry --skill channel-name-parsing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Parsing CHANNELNAMES.txt files across microscopy systems can be inconsistent. This Skill auto-detects formats and extracts channel names per cycle for robust labeling.

Core Features & Use Cases

  • Auto-detects and parse four formats: Simple List, Cycle-Prefixed, Tab-Separated, and CSV.
  • Returns a mapping of cycle numbers to channel names for downstream labeling.
  • Example usage with a sample meta directory to produce channel dictionaries.

Quick Start

Call load_channel_names(meta_dir) to obtain a dict like {1: ["DAPI", "Blank", "Blank", "Blank"], 2: ["DAPI", "CD31", "CD8", "CD45"]}. If no file is found, fall back to a manual definition.

Frequently Asked Questions about channel-name-parsing

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

FAQPage Schema
How do I parse channel names from CHANNELNAMES.txt files in microscopy data?▼

Parse CHANNELNAMES.txt by auto-detecting its format—simple list, cycle-prefixed, tab-separated, or CSV—then extract channel names per cycle. Call load_channel_names(meta_dir) to return a mapping like {1: ["DAPI", "Blank"], 2: ["DAPI", "CD31"]}, ready for downstream labeling in microscopy pipelines.

What formats does CHANNELNAMES.txt parsing support?▼

Format detection handles four conventions: simple lists, cycle-prefixed formats, tab-separated columns, and CSV. The parser auto-identifies the structure, extracts DAPI-based cycle boundaries, handles variable channels per cycle, and ignores comments to produce a consistent cycle-to-channels mapping.

Can I use this parser with CODEX microscopy data?▼

Yes. The parser applies to CODEX-like microscopy data pipelines that output CHANNELNAMES.txt. It auto-detects CODEX and related format conventions, extracts per-cycle channel labels, and returns structured mappings for robust channel labeling downstream.

What happens if my CHANNELNAMES.txt file isn't recognized?▼

If the parser cannot detect a supported format or find the file, it returns no result. Fall back to manual channel name definition in your pipeline to ensure labeling continues uninterrupted.

How do I handle variable numbers of channels across cycles?▼

The parser natively handles variable channels per cycle by extracting the full channel list for each detected cycle, preserving structure differences. Each cycle maps to its own channel-name list regardless of length differences between cycles.