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rh-inf-ingest

Plan and execute end-to-end clinical source ingestion workflows via the rh-skills CLI.

12|1|Updated Apr 15, 2026
Search Tags:#markdown#data-pipeline#ingest#annotation#clinical-informatics#topic-inference
One-click install
npx skills add https://github.com/reason-healthcare/rh-skills --skill rh-inf-ingest
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rh-inf-ingest
Source: https://github.com/reason-healthcare/rh-skills/tree/main/skills/.curated/rh-inf-ingest
Command: npx skills add https://github.com/reason-healthcare/rh-skills --skill rh-inf-ingest

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrate end-to-end ingestion of clinical sources by coordinating discovery, download, normalization, topic inference, classification, and annotation to produce ready-to-use artifacts for downstream computable rules.

Core Features & Use Cases

  • Deterministic, CLI-driven workflow for source intake: downloads, normalization to Markdown with frontmatter, topic initialization, and artifact generation.
  • Idempotent operations across plan/implement/verify modes, with clear handling for open, authenticated, and manual sources.
  • Production-ready pipeline for HI evidence synthesis, enabling downstream extraction, formalization, and concept vocabulary generation.
  • On-demand resources management and strict CLI-only I/O to maintain reproducibility and traceability.
  • Example use: ingest a set of open sources to produce sources/normalized files and a topics/<topic>/process/concepts.yaml for L2/L3 processing.

Quick Start

Plan and run an end-to-end ingest for a topic using rh-skills ingest plan <topic> followed by rh-skills ingest implement <topic>.

Frequently Asked Questions about rh-inf-ingest

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

FAQPage Schema
How do I automate clinical data ingestion and normalization for downstream processing?▼

Clinical data ingestion automates downloading raw sources, normalizing content into Markdown with frontmatter, and running topic inference to produce computable artifacts and a de-duplicated concepts.yaml file.

What is topic inference and classification in a clinical data pipeline?▼

Topic inference and classification categorize ingested clinical sources during normalization, initializing topics and generating annotated outputs ready for downstream computable rule extraction.

How do I run an end-to-end clinical source intake workflow using a CLI?▼

Run rh-skills ingest plan <topic> followed by rh-skills ingest implement <topic> to execute deterministic, idempotent clinical source intake workflows via the CLI.

Does this data pipeline support idempotent operations for both open and authenticated sources?▼

Yes, the ingestion pipeline enforces idempotence across plan, implement, and verify modes, handling both open and authenticated clinical sources with soft-fail behavior when necessary tools are missing.

Can I process manual clinical sources through this ingestion workflow?▼

Yes, the ingestion workflow provides clear handling for open, authenticated, and manual clinical sources, maintaining strict CLI-only I/O to ensure reproducibility and traceability.

What are the limitations when required CLI tools are missing during source intake?▼

When necessary tools are missing, the ingestion pipeline exhibits soft-fail behavior, allowing the workflow to continue gracefully while maintaining strict CLI-only I/O for reproducibility.

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