oma-scholar

Generate and validate Knows v0.9.0 `.knows.yaml` research-paper sidecars.

46|2|Updated Mar 23, 2025
One-click install
npx skills add https://github.com/gracefullight/krds --skill oma-scholar-gracefullight
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: oma-scholar
Source: https://github.com/gracefullight/krds/tree/main/.agents/skills/oma-scholar
Command: npx skills add https://github.com/gracefullight/krds --skill oma-scholar-gracefullight

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Scholarly research workflows need fast, structured access to paper claims, evidence, and relationships, but PDFs and unstructured notes are slow to interpret and validate.

Core Features & Use Cases

  • Knows sidecar generation from academic sources: create v0.9.0 .knows.yaml structured research-paper sidecars that expose claims, evidence, relations, and provenance for token-efficient downstream use.
  • Validation and quality checking: lint generated or fetched sidecars to ensure schema correctness, ID integrity, enum compliance, and anti-fabrication constraints before sharing.
  • Remote discovery and querying (knows.academy + OpenAlex fallback): search and fetch existing sidecars (or metadata + abstracts when missing) to support literature search, synthesis, comparison, and peer-review style outputs.

Quick Start

Ask the AI to: generate and validate a .knows.yaml sidecar for the paper you provide, using the Knows .knows.yaml spec and the oma scholar workflow (including linting).

Frequently Asked Questions about oma-scholar

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

FAQPage Schema
How do I convert academic papers into structured YAML metadata?

You convert academic paper content into structured `.knows.yaml` research-paper sidecars by generating records that expose claims, evidence, relations, and provenance for token-efficient downstream use.

How do I validate schema correctness for generated research paper sidecars?

You validate generated `.knows.yaml` sidecars by linting them to ensure schema correctness, ID integrity, enum compliance, and anti-fabrication constraints before sharing or downstream processing.

Can I use OpenAlex to fetch metadata and abstracts for missing paper sidecars?

Yes, you can search and fetch existing sidecars from knows.academy, with an OpenAlex fallback to retrieve metadata and abstracts when sidecars are missing for literature synthesis.

What is the best way to summarize claims and evidence from scholarly literature?

Summarizing claims and evidence from scholarly literature is best handled by generating structured sidecars that expose provenance, supporting token-efficient evidence-first workflows for analysis.

Does peer-review sidecar creation require strict schema rules and anti-fabrication guardrails?

Yes, peer-review sidecar creation requires strict Knows `.knows.yaml` spec compliance, deterministic lint-based validation, and anti-fabrication guardrails to prevent unverified data.

What are the limitations of unstructured PDF notes compared to structured sidecars?

Unstructured PDF notes are slow to interpret and validate, whereas structured `.knows.yaml` sidecars provide deterministic schema compliance and immediate access to claims and evidence relationships.