Extract job requirements
The workflow turns the job description into structured role facts, including responsibilities, skills, technologies, and recurring keywords.
The workflow separates job requirements, career evidence, missing proof, and final wording so you can inspect how a tailored resume was assembled.
The workflow turns the job description into structured role facts, including responsibilities, skills, technologies, and recurring keywords.
Each requirement is compared with the imported master resume. The evidence map records which experience supports the requirement and where the support came from.
Requirements without enough evidence remain visible. The workflow can ask a targeted question, but the user decides whether a factual answer exists.
Supported evidence is organised into a job-specific resume draft. The user can edit the wording before exporting PDF or DOCX.
The current score is calculated as matched extracted terms ÷ total extracted terms, rounded to a percentage. A term counts as matched when it appears in the current normalised resume draft. It measures keyword presence, not how many job requirements have supporting career evidence.
In the worked demonstration, the visible draft contains 6 of 8 explicitly listed terms: 6 ÷ 8 × 100 = 75%. That example uses a fixed, illustrative term list so you can reproduce the calculation.
The evidence map asks which source facts support each responsibility, skill or qualification. A requirement can have sufficient evidence, partial support, or a gap. This assessment is separate from finding the same word in a draft.
The worked example has 2 supported requirements, 1 with partial evidence, and 2 gaps. “Design” appears as a collaborating team, but no experiment design is recorded. Product launches cannot be rewritten as experiments.
Inspect the source facts and every requirement →Review the inputs, evidence map, missing proof, tailored bullet, and score boundary.
View the worked example