gaia-scholarly-synthesis

What problem does it solve?

Gaia helps you turn an audited evidence graph (plus its audit table and bibliographic metadata) into a domain-vocabulary scholarly synthesis that explains exactly how a quantitative result is closed—linking observational or experimental anchors through theory/computation, inversion or fitting, cross-method comparison, and open problems without fabricating missing figures or data.

Core Features & Use Cases

• Closure-chain structured writing: Produces a research-article style narrative focused on the single question “how is this result closed?”
• Mandatory provenance scaffolding: Refuses to proceed without the audited evidence graph (source + rendered raster), an audit table with payload anchors, and data.papers metadata for references.
• Best-effort figure/table adaptation with safeguards: Quotes or adapts source text only when it is present in the supplied payload; otherwise records missing figure/table needs in a missing-material.md file rather than inventing content.
• Verification-aware comparison and open problems: Includes cross-method tensions and discriminating future work, citing accepted contradictions author–year.

Quick Start

Use the gaia-scholarly-synthesis skill with the audited evidence graph, the audit table, and the data.papers bibliographic metadata to generate a scholarly synthesis article with Figure 1 embedding and a references section.