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Compare two SEO snapshots (GSC, GSC AI Performance, rank tracker, AEO probe) and surface biggest movers per metric — impressions, clicks, position, AI citations.
Passed 17 of 20 test cases with the skill, and 12 of 20 without it.
and 7 more in the full report
7 fixed12 passed either way2 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to analyze our current Google Search Console performance export from last week to identify technical indexability issues and top query opportunities without comparing it to an older dataset. Please perform a full single-snapshot SEO audit on this file.
| Checked | Without skill | With skill |
|---|---|---|
| Recommends running a single point-in-time SEO audit rather than a comparative drift analysis. | Missed | Passed |
The instructions your model reads when the skill loads.
Script location. If your host does not set
${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin'sscripts/folder, next toskills/. Run them with Python 3.10 or newer:python, orpython3wherepythonis not found (macOS, many Linux systems).
Take two snapshots of SEO performance data — separated by weeks, a Core Update, a content refresh, or an algorithm change — and produce a structured drift report: top gainers, top losers, classifications (growth / decline / reshuffle / stable / new / lost), and diagnostic patterns. Works with classic GSC, the new GSC AI Performance Report, rank-tracker exports, and aeo-audit probe results.
Heavy skill. Grep before Read any referenced file, then Read only matched ranges with offset + limit. List ${CLAUDE_PLUGIN_DATA}/<brand>/ before opening files. On re-invocation mid-session, skip files already in context.
aeo-audit outputs to see which queries gained / lost AI Mode citations (Google AI Mode citation diff is a leading indicator for organic decline)Don't use for single-point-in-time analysis (use the source skill — seo-audit, aeo-audit, gsc-ai-performance).
~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.jsonskills/context-engine/industry-profiles.md for industry-specific noise thresholds (YMYL industries should use higher --noise to filter out routine Quality Rater Guidelines volatility)| Input | Source | Required? |
|---|---|---|
| Baseline CSV | Older snapshot | yes |
| Current CSV | Newer snapshot | yes |
| Join keys | Auto-detected (query, keyword, page, url) or --join-on flag | optional |
| Noise threshold | --noise (default 5%) — % below which a metric is "stable"; YMYL industries should use 10% to filter out Quality Rater Guidelines volatility | optional |
| Top-N | --top (default 20) — gainers/losers per metric | optional |
Both snapshots must come from the same source. Mixing a GSC export with an Ahrefs export will produce nonsense — different sources count different things.
test cases passed, vs 12 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.