job-cold-prospect

Cold prospecting is automated by researching the target company, tailoring your CV, generating speculative letters and LinkedIn outreach, and compiling a company dossier. It reuses shared master CV resources and fact-base extraction to ensure fact-grounded, auditable artifacts.

Yes, LinkedIn outreach is generated by crafting two message variants per leadership contact identified during company research. These messages are anchored in verified company facts and aligned with your selected role angle for targeted speculative applications.

Tailoring a CV for speculative outreach uses fact-base extraction from company research to select a specific role angle. It adapts your shared master CV to align with the target company's verified facts and narrative approach.

Speculative applications maintain an audit trail by preserving all prep artifacts and sources during generation. The workflow creates an entry in the shared job_history DB, validates schemas, and ensures artifacts are auditable for later status updates.

Dependencies like python-docx and jsonschema are required to generate document artifacts and validate schemas within the cold prospecting workflow. They ensure the produced speculative letters, CVs, and dossiers conform to expected formats and data structures.

The cold prospecting workflow shares infrastructure with job-application-tailor for consistency, meaning it requires the same shared master CV and history DB. It relies heavily on accurate company research and fact extraction, limiting output quality if target company data is sparse.