Ingest Router

Detect content formats and route them to specialist ingestion skills.

14|2|Updated Feb 27, 2026

Search Tags:#routing #ingestion #slack #rfc #content processing #data structuring #signal

Ready to run

npx skills add https://github.com/rchandnaWUSTL/pm-digital-twin --skill ingest-router

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Ingest Router
Source: https://github.com/rchandnaWUSTL/pm-digital-twin/tree/main/skills/ingest-router
Command: npx skills add https://github.com/rchandnaWUSTL/pm-digital-twin --skill ingest-router

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automatically detects the format of raw text content (like Slack threads, RFCs, or signals) and routes it to the appropriate specialized ingestion skill, ensuring consistent structuring and file path management.

Core Features & Use Cases

Auto-detection: Identifies content type (Slack, RFC, Signal) using pattern heuristics.
Content Structuring: Generates frontmatter, extracts project tags, and creates filesystem-safe slugs.
Delegation: Passes content to specialist skills for detailed parsing and saving.
Use Case: Paste a raw customer email into the system, and the Ingest Router will identify it as a 'field signal', extract the customer name and project, and save it to the correct location with appropriate metadata, ready for further analysis.

Quick Start

Ingest the following content as a Slack thread: "Hey team, let's discuss the new feature launch..."

Frequently Asked Questions about Ingest Router

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

FAQPage Schema

How do I automatically route Slack threads and RFCs into structured markdown files?▼

To route Slack threads and RFCs into structured markdown, you need an ingestion pipeline that auto-detects content formats, extracts project tags, generates filesystem-safe slugs, and delegates parsing to specialist skills for consistent file path management.

What is the best way to structure unstructured Slack threads and field signals for analysis?▼

Structuring unstructured Slack threads and field signals requires a unified ingestion router that applies pattern heuristics to detect content types, generates frontmatter, and saves the data to correct locations with appropriate metadata for analysis.

How does content auto-detection work for routing semi-structured data like RFCs?▼

Content auto-detection for routing semi-structured data like RFCs uses pattern heuristics to identify the source format, extract relevant project tags, and generate collision-free slugs before delegating the content to a specialized ingestion skill.

Can I ingest raw customer emails as field signals and extract project tags automatically?▼

Yes, you can ingest raw customer emails as field signals. The system identifies the content as a field signal, extracts the customer name and project tags, and saves it to the correct location with appropriate metadata for further analysis.

Does the content routing pipeline handle file path collision detection for markdown files?▼

Yes, the content routing pipeline handles file path collision detection during the ingestion process. It generates filesystem-safe slugs and manages file paths to ensure structured markdown files are saved without overwriting existing data.

When do I need a unified ingestion pipeline for content processing?▼

You need a unified ingestion pipeline for content processing when handling diverse unstructured and semi-structured formats like Slack threads and RFCs, ensuring they are standardized into structured markdown files with consistent frontmatter and metadata.