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Evidence-based resume writing from a codebase requires analyzing stack, architecture, and quality indicators to extract demonstrated skills, classifying proficiency levels honestly, and blocking unsupported claims like revenue impact or real-user metrics to ensure non-fabrication.

Generating a portfolio from a code repository involves summarizing the project from code, extracting demonstrated skills, and producing portfolio entries tailored to recruiter audiences, while enforcing privacy constraints to avoid disclosing proprietary internal details.

Evidence-based career documentation transforms a software codebase into credible resumes and portfolios by applying evidence-first analysis of stack, architecture, and features, enforcing non-fabrication, and clearly separating demonstrated versus inferred claims for recruiter audiences.

Assessing demonstrated skill proficiency from a codebase involves analyzing the depth of technology usage and classifying skills into expert, proficient, familiar, or exposure levels based on demonstrated depth, ensuring skill statements match actual code evidence.

Codebase analysis for resume writing applies strict privacy and anti-fabrication guardrails to prevent disclosing secrets or proprietary internal details, blocking unsupported claims like revenue impact or real-user metrics unless explicitly supported by code evidence.