skill-3-concern-match-graph

To build a match graph for alignment gaps, provide two canonicalized YAML concern sheets for a given paper or version. The skill generates cross-source matches with explicit labels, severity alignment, and rationales for each edge.

A concern match graph is a structured network mapping official issues to agentic concerns. You need it for research calibration and error analysis when diagnosing divergence between extracted concern sheets from different sources.

Generate cross-source matches by supplying canonicalized concern statements and a defined match_graph schema. The skill processes these structured inputs to produce matches labeled as exact, partial, or related with judgment alignments.

Yes, canonicalized concern statements are required as structured inputs. The skill needs predefined canonical issue descriptions alongside a defined match_graph schema to produce accurate matches with judgment alignments.

Yes, provide two YAML concern sheets representing official and agentic perspectives. The skill produces a structured match graph that includes severity alignment data and rationales to diagnose where the concern sources diverge.

The match graph depends entirely on the quality of pre-extracted concern sheets. It requires canonicalized statements and a predefined schema, meaning it cannot generate matches from unstructured text or raw paper inputs directly.