Example output. Your real review uses your own resume and the JD you paste.
ATS BY THE NUMBERS
15-25
ATS keywords per SWE resume is the modern target
60-80%
coverage of the JD's keyword set is the scoring threshold for first-cut survival
10.6x
increase in interview likelihood when your resume includes the exact job title from the posting
Around 90% of large employers use applicant tracking systems to parse, score, and rank resumes before any human reads them. The bot reads top-to-bottom, maps your text into structured fields, and scores against the job description. The way to "beat" the bot is to be one of the resumes the recruiter's filter surfaces, which means matching the JD's keywords precisely and being parseable as structured data. The widget above runs that scoring on your resume against the JD you paste, in 30 seconds.
Languages: name them, don't list them
Bullets that say "Built X in Go" beat a Skills block that lists 12 languages. ATS weights in-context keywords higher than skill-block keywords.
Named framework signal
React, Next.js, gRPC, FastAPI, Spring Boot, Express, Django, Rails. Generic "web frameworks" fails the keyword match.
Named system signal
Kafka, RabbitMQ, Postgres, MySQL, Spanner, DynamoDB, Redis, ElasticSearch, S3. Generic "databases" loses to the named one.
Named practice signal
On-call, CI/CD (with the specific tool: GitHub Actions, CircleCI, Jenkins), observability (with the tool: Datadog, Prometheus, Grafana), idempotency, blue-green deploys.
Quant outcomes per bullet
Every bullet should end with QPS, p99 latency, uptime %, MTTR, $-saved, or users served. ATS flags verb-only bullets ("Helped with...") as content-light.
Cloud platform specificity
AWS, GCP, Azure with the specific services (ECS, Lambda, GKE, Cloud Run, Aurora). Generic "cloud experience" fails the match.
Architecture vocabulary
Microservices, event-driven, distributed, async, REST, GraphQL, gRPC, WebSocket. Surface the ones that match the JD.
Concurrency / safety vocabulary
Thread-safe, lock-free, ACID, idempotent, exactly-once, eventually-consistent. Modern SWE JDs name these explicitly.
1. Upload your resume
DOCX or text-selectable PDF only. Image-based PDFs cannot be read by any ATS. 10MB max.
2. Paste the job description
Full JD text or the URL of the posting. The score is tailored to that exact JD.
3. Apply the rewrites
Critical and Notable edits are grouped by severity. Each shows the original, the rewrite, and which keyword or formatting rule it fixes.
4. Download the new PDF
The preview rebuilds your resume live as you accept edits. Single-column, Workday-safe, ready to submit.
NOT APPLYING YET?
Every Monday: the specific ATS keywords showing up in newly posted JDs at Goldman, McKinsey, Google, and 20 other firms. Free, no spam.
15 to 25 relevant keywords with 60-80% coverage of the JD's keyword set. More than 25 reads as keyword stuffing; modern ATS 2.0 platforms flag it.
Yes, but treat it as backup. ATS weights in-context keywords (mentioned inside Experience or Projects) higher than Skills-block-only keywords. Lead with in-context.
Yes. The JD keyword match is JD-specific. A bullet that hits the Stripe keyword set might miss the Google one because they call out different tools.
"Agile" and "Scrum." Every JD lists them and every resume includes them, so they no longer differentiate. Replace with the actual tool you used (Jira, Linear, Shortcut).
"On-call." Bullets that mention on-call rotation, incident response, or production debugging signal real-world experience that intern-only resumes lack.
New grad: weight projects + coursework heavier. Mid (L4-L5): weight named systems + scope. Senior (L6+): weight architecture decisions, cross-team ownership, mentorship.
No catch. Upload your resume, paste the SWE JD, get the score and missing keywords without an account.
Yes, but those have separate dedicated keyword pages with the named ML frameworks and named eval methodologies they look for.