This page provides a practical checklist and assessment template aligned to the Technical SEO Skills Framework. It is designed for hiring managers, team leads, and individuals who want to measure skills objectively and plan development activities.
Use the checklist to assess current skills, identify gaps, and prioritize learning tasks. For each item, score proficiency as: 0 = No experience, 1 = Basic, 2 = Competent, 3 = Advanced. Collect artifacts as evidence: PRs, reports, scripts, diagrams, or screenshots. Use the summed scores to identify priority domains for development.
The checklist below is organized by the common framework domains. Each bullet is an assessable skill with suggested evidence types.
Crawling & Indexing
Robots.txt and meta directives — Evidence: configuration file and test results
Sitemap strategy and automation — Evidence: generated sitemap examples and submission logs
Canonical tag implementation — Evidence: sample pages and canonical audit
Redirect mapping and rules — Evidence: redirect map and implementation PRs
Rendering & JavaScript SEO
SSR vs CSR decisions and tradeoffs — Evidence: architecture notes and before/after indexing tests
Hydration and critical content exposure — Evidence: audit screenshots and rendering test scripts
Using prerendering or dynamic rendering when necessary — Evidence: implementation notes
Performance & Core Web Vitals
Optimizing LCP, CLS, INP/FID — Evidence: Lighthouse reports and implemented fixes
Image and asset pipelines — Evidence: image optimization scripts
Cache policies and CDNs — Evidence: CDN configuration reviews and metrics
Structured Data
Product, Article, Breadcrumb schema — Evidence: markup snippets and Search Console results
Automated schema validation in CI — Evidence: test logs
Monitoring & Diagnostics
Log analysis and crawl telemetry — Evidence: example queries and findings
Search Console and analytics integration — Evidence: dashboards and anomaly detection rules
For each candidate or team member, complete a table with domain, skill item, score (0–3), evidence reference, and suggested development action. Sum the domain scores and set target improvements for the next quarter. Use project-based tasks as remediation steps rather than passive learning alone.
Technical proficiency should be complemented by collaboration skills. Assess whether the person documents work clearly, communicates tradeoffs effectively, and drives cross-team alignment. Evidence includes design docs, meeting notes, and stakeholder feedback.
Good projects are scoped, measurable, and tied to production telemetry. Examples: fix a persistent CLS issue on five high-ranking templates, implement server-side rendering for a dynamic landing page and measure indexing changes, or create CI checks that prevent pushing templates with missing structured data.
After scoring, identify domains with the largest gaps and select 1–3 focused projects for the next 90 days. Pair less experienced staff with senior mentors for each task. Track progress with artifact submissions and measurable before/after metrics.
Translate scored outcomes into hiring benchmarks. For example, a mid-level role might require at least a competent score (2) across Crawling & Indexing and Rendering, plus evidence of one automation project. Create sample assignment briefs that candidates can complete in a timed take-home exercise or during a paid trial.
This checklist and assessment approach is designed to be pragmatic, evidence-driven, and adaptable to different organizational sizes. Regularly review and update it as search engine features evolve, and keep assessment artifacts centralized for transparency and continuous improvement.