Resume ↔ Job Description Matcher — fit score + gap analysis

How fit scoring works

The matcher reads both inputs: your resume PDF and the JD text you paste. It identifies the JD's explicit requirements (years of experience, specific tools, certifications, domain experience), implicit skills (skills the JD implies are needed but doesn't list explicitly), seniority signals (title alignment, scope of responsibility), and domain keywords (industry-specific terminology). Then it scores your resume against each dimension.

The final score is a weighted combination: 50% explicit requirements (the JD's stated must-haves), 25% inferred skills (what the JD implies you need), 15% seniority/title alignment (match between your past titles and the target role's level), 10% domain keywords (industry-specific terminology overlap).

Three score ranges and what they mean

The score-to-decision mapping:

• 80-100 — strong fit, apply. Most explicit requirements met; the resume shows the relevant experience. Apply with confidence. Tune the cover letter to match the JD's specific concerns; the bulk of the alignment work is done.
• 65-80 — partial fit, apply with tailoring. Some explicit requirements met but gaps exist. Worth applying with a tailored cover letter that explicitly addresses the gaps. The cover letter does the work the resume can't — explaining transferable experience or willingness to grow into specific gaps.
• Below 65 — significant gap, reconsider. Substantial gaps in either requirements, seniority, or domain. Sometimes worth applying anyway (mid-career pivot, networking-driven opening) but the base rate of success is low. Consider whether the gaps close easily (add a line to the resume) or require real experience (skip and target roles where the fit is stronger).

The per-requirement table is what's actually actionable

The score is a number; the table is the work. Three things the per-requirement table surfaces:

• Met requirements with evidence. Each JD requirement matched to specific resume content. "5+ years Python experience required" → "Resume shows 6 years across companies X and Y." Confirms the strength so the cover letter can reinforce it rather than re-state it.
• Partially-met requirements. JD requires X, resume shows X-adjacent. "5+ years Python" → "Resume shows 3 years Python + 4 years Ruby." The cover letter has an opportunity to bridge — explain how Ruby experience transfers, mention recent Python upskilling, etc.
• Unmet requirements. JD requires X, resume shows nothing matching. Hard gaps. The cover letter has to either acknowledge or work around. Some gaps are dealbreakers; others are negotiable. The table makes the gaps explicit so you can decide.

Missing ATS keywords — the filter that blocks you before recruiter review

Most large companies filter applications through an ATS before any human review. ATS filters search for specific keywords from the JD. Missing keywords = filtered out before recruiter sees the resume.

The matcher surfaces JD-critical terms (tools, certifications, acronyms, domain terms) and flags which ones are absent from the resume. Three patterns:

• Add keywords you ALREADY HAVE experience with. If the JD mentions "AWS" and your resume says "deployed services on Amazon Web Services," you have the experience but ATS is looking for the exact term. Add "AWS" explicitly.
• Don't add keywords you don't have experience with. Stuffing keywords with no underlying experience trips ATS keyword-density flags AND fails at recruiter review. Honest tuning only.
• Match terminology to the JD exactly. If the JD says "Postgres" and your resume says "PostgreSQL," ATS may not match them. Match the JD's spelling unless your resume serves many different roles with different conventions.

Three workflows where the matcher earns its place

Specific use cases:

• Pre-application decision. Decide whether a specific role is worth applying to before investing time in a tailored cover letter. Score above 65: yes. Below: probably not.
• Cover-letter tailoring. Once you've decided to apply, the per-requirement table tells you what the cover letter needs to address. Specifically the partially-met and unmet rows — those are what the cover letter is for.
• Resume tuning for a specific role. Where the resume has experience that matches the JD but doesn't surface it explicitly, tune the resume's bullet points to use the JD's terminology. Run the matcher again to confirm the tuning improved the score.

What the score isn't

Three limits worth knowing:

• Not a hiring decision. An 85 doesn't guarantee an interview; a 60 doesn't guarantee rejection. Hiring includes factors the matcher can't see (referral connections, hiring-manager preference, company-specific signals).
• Not a substitute for understanding the role. The matcher reads the JD literally. If the JD has hidden expectations not stated in writing (common in less-explicit job descriptions), the score reflects the explicit JD only. Talk to recruiters or current employees for the implicit picture.
• Not predictive of your performance in the role. Fit-to-JD ≠ fit-to-actual-job. The JD is the recruiter's compressed best-guess of what's needed; the actual role has more nuance. The score predicts "likely to pass screening," not "likely to succeed."

Limits and pricing

Resume ↔ JD Matcher charges 5 credits per match. The tool handles resume PDFs up to 25 MB and JD text of any reasonable length. Processing runs on our servers; the resume and JD are in memory only during analysis and are never persisted by default. Pro tier offers 30-day history for tracking multiple JDs.

Common pairings: ATS Resume Optimizer first (verify resume parseability), then JD Match (verify role fit), then Cover Letter Generator (produce the tailored letter). The three together cover the full pre-application workflow.