commonground-scenarios

Deterministic, offline scenario generation for the Common Ground environment family. Each generated scenario contains a fictional organization, policy documents, planted ambiguities/contradictions/gaps, precise distractors, a seeded persona panel, and provenance.

Every canonical clarifying question is phrased as a yes/no proposition and declares whether “yes” selects its primary anchor or an alternative. agree predicts yes, disagree predicts no, and pass means the faction takes no position. Stances are composed from issue-independent faction values and an issue-specific value trade-off, then oriented to that declared polarity. Canonical wording and aliases remain authoring metadata, not hidden lexical requirements in environment scoring.

The default generator uses committed templates only. An operator may inject a prose-polishing callback, but no model client or network path is built into the package, and validation requires every planted anchor to survive polishing.

Training and held-out template registries and template/layout-profile labels are disjoint. The canonical release contains 100 training and 100 held-out rows. The generator assigns opaque document/faction IDs, varies visible layout and faction count/order, and records general faction values, question polarity, answer-conditioned value, and explicitly authored paired evidence for every contradiction. Validation rejects inferred or aliased relationships that collide with another planted issue or distractor. Split generation distinguishes exact instance, canonical prompt, and policy-issue fingerprints; it also runs token-Jaccard and word-ngram TF-IDF cross-split neighbor audits. Generated scenarios are canonical JSON and regenerate byte-for-byte from the same template, seed, and explicit generation date.

The bundled scenarios are synthetic. The optional human_feedback field supports advanced custom input and delegates to the shared fail-closed validator. It is not used by the bundled data; see human-data governance for its separate review requirements.

The packaged Draft 2020-12 schema has the stable identifier urn:commonground:schema:scenario:3 and is available through load_scenario_schema.