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.
