What problem does it solve?
Scholarly Markdown documents often contain claims, evidence, questions, protocols, and requests that are not machine-readable, making it hard to trace which evidence supports which claim. This Skill adds semantic MIRA research-object annotations directly into the source Markdown without rewriting the author's wording.
Core Features & Use Cases
- Research Object Annotation: Identifies and wraps claims, typed claims (hypothesis, theorem, proposition), evidence, questions, protocols, and requests using syntax idiomatic to the document's Markdown flavor.
- Multi-Dialect Support: Detects and applies the correct syntax for Stencila Markdown (.smd), Quarto (.qmd), MyST (.myst), and plain Markdown (.md), preserving frontmatter, code cells, citations, and math.
- Relation Encoding: Adds source-local relations such as supports, supported-by, opposes, addresses, and grounds as attributes pointing to unique kebab-case object ids.
- Use Case: Given a Quarto manuscript with results and conclusions, annotate each conclusion as a claim linked via supported-by to the corresponding evidence block, producing a semantically structured document ready for Stencila publishing.
Quick Start
Annotate the attached manuscript.qmd with MIRA claims, evidence, and their supporting relations while preserving all Quarto syntax.