SEO Traffic Analyzer

SEO Traffic Analyzer

The explicitly free, no-paid-tool SEO skill. Everything is serp-derived by design via serp_probe.py, the SimilarWeb free page, and Wayback; paid tools are optional supplements. You, the agent, organize keywords into buckets, find content gaps, and write the report.

When to use

• "Analyze SEO and traffic for [domain]." / "Where does [domain] rank for [keywords]?"
• "Compare [domain]'s SEO against [competitors]." / "Find content gaps vs competitors."
• The free SEO layer for competitive landscape work and company-current-gtm-analysis.

How to run

1. Site indexation & structure (keyless)

python3 ${SKILL_DIR}/scripts/serp_probe.py site --domain example.com \
  --output ${WORKSPACE}/indexed.json
# also probe structure with refined site: queries via the search subcommand, e.g.
python3 ${SKILL_DIR}/scripts/serp_probe.py search --query "site:example.com blog" \
  --output ${WORKSPACE}/blog_pages.json

2. Keyword ranking probes (brand / category / problem / competitor buckets)

python3 ${SKILL_DIR}/scripts/serp_probe.py search --query "rpa platform" \
  --target-domain example.com --output ${WORKSPACE}/kw_category.json

Record presence / approximate position, ranking URL, and co_ranking_domains per keyword. Auto-infer keywords from domain content + your knowledge if none are provided; expand category/problem/brand variants yourself.

3. Traffic estimation

npx playwright install chromium   # first run only
node ${SKILL_DIR}/scripts/render_page.mjs \
  --url "https://www.similarweb.com/website/example.com/" --wait 6000 \
  --output ${WORKSPACE}/similarweb.json
python3 ${SKILL_DIR}/scripts/wayback_fetch.py --url https://example.com \
  --snapshots 5 --output ${WORKSPACE}/wb.json     # snapshot frequency = activity signal

Also use serp_probe.py search --query '"example.com" -site:example.com' for the referral footprint. Report traffic as labelled estimates; if SimilarWeb is rate-limited, note reduced confidence.

4. Backlink & authority signals (keyless)

Web-search for press mentions, awards, and directory listings (G2, Capterra, Product Hunt, AlternativeTo); categorize the linking domains. Exact numbers need a paid source (optional).

4b. (Optional) Enrichment — measured metrics (paid, off by default)

This skill is free, no-paid-tool BY DESIGN; the keyless flow is and stays the DEFAULT. Only if DATAFORSEO_LOGIN/DATAFORSEO_PASSWORD are set, the bundled DataForSEO adapter can replace the labelled estimates with MEASURED traffic/authority/backlinks/ranked keywords:

python3 ${SKILL_DIR}/scripts/paid_seo.py domain --domain example.com \
  --output ${WORKSPACE}/paid_domain.json         # measured authority rank + organic traffic
python3 ${SKILL_DIR}/scripts/paid_seo.py ranked --domain example.com --limit 100 \
  --output ${WORKSPACE}/paid_ranked.json          # real ranking keywords + per-keyword volume
python3 ${SKILL_DIR}/scripts/paid_seo.py backlinks --target example.com \
  --output ${WORKSPACE}/paid_backlinks.json       # referring domains, backlinks, domain rank

If creds are absent the adapter prints "paid enrichment unavailable — keyless path still applies" and exits non-zero without breaking this flow — skip it; the free report is complete. When the JSON IS produced, merge it and upgrade the "estimate" labels to "measured" (traffic, authority, exact backlink/referring-domain counts, ranking keywords). The content-gap analysis remains the highest-value output regardless. (Semrush/Ahrefs are alternative providers — not implemented in the adapter.)

5. Competitive comparison + content gaps

Repeat steps 1–2 per competitor; build a keyword × domain matrix. For gaps, probe serp_probe.py search --query "site:<competitor> [keyword]" — keywords/topics where competitors rank but the target doesn't, and missing content types (comparison pages, use cases, calculators, integrations, case studies, glossary).

6. Report (you, the agent — no script)

Write the markdown report: executive summary, site indexation/structure, keyword rankings by bucket, traffic estimates + sources, competitive comparison matrix, content-gap analysis, SWOT-style assessment, and prioritized recommendations. Report positions as page-1 presence/approximate rank; traffic as labelled estimates.

Outputs

• ${WORKSPACE}/indexed.json, kw_*.json, similarweb.json, wb.json — collected signal.
• The SEO report (markdown) returned as result / saved to --output_path if provided.

Credentials / env

• Required: none — the entire capability is serp + browser + Wayback + agent. Free by definition.
• Optional: DATAFORSEO_LOGIN/DATAFORSEO_PASSWORD enable the bundled scripts/paid_seo.py enrichment (Step 4b) — measured traffic/authority/backlinks/ranked keywords that upgrade the estimate labels to "measured". A bring-your-own Semrush/Ahrefs key (no Robomotion package — alternative, not wired into the adapter) or APIFY_API_TOKEN (Semrush/Ahrefs-scraper actor) are further options. The report is complete without any of them.

Notes & edge cases

• Traffic estimates are rough and exact positions can't be pinned — report page-1 presence and approximate rank, label estimates, never present them as precise tool metrics.
• SimilarWeb free tier is rate-limited; if blocked, lean on search-volume inference + referral signals and note reduced confidence.
• Content-gap analysis is the highest-value output — comparison pages are usually the top-ROI gap for B2B SaaS.
• Results vary by geography/personalization — state the country/language assumption.
• Brand-keyword monitoring matters: if a competitor ranks/bids on the target's brand terms, flag it.
• serp_probe.py uses a keyless public HTML SERP endpoint that can rate-limit; in a Robomotion deployment swap it for the robomotion-serp Search node (proxy + geo).