academic-voice

Capturing an author's voice before academic drafting involves ingesting a canonical author profile and running a HITL interview to create a piece-specific voice fingerprint. This ensures academic drafts sound authentic from the very first word rather than generic.

Voice context generation is a pipeline stage that combines an author's enduring standing voice with article-specific motivations. It produces a voice_context.json file containing both inputs, enabling authentic tone adoption during the Stage 6 drafting phase.

To prevent generic academic drafts, read a canonical author voice profile from your vault to apply durable style rules. The profile path is recorded in the output file, ensuring consistent voice reuse across multiple academic drafting runs.

An academic voice interview collects eight targeted answers covering the trigger, evidence, contrarian take, authority, specific reader, business connection, call to action, and emotional core. These inputs create a detailed voice fingerprint for the specific article.

Voice context generation integrates into an academic pipeline workflow after perspective building and before academia formatting. Run it with the Stage 2 perspective.json to produce the required voice_context.json file in the run folder's pipeline directory.

A vault voice profile is required to supply the author's standing voice rules for academic writing. If unavailable, the profile must be resolved before the eight HITL prompts can be collected to complete the voice_context.json output.