seo-drift
Compare two SEO snapshots from the same source — GSC, the GSC AI Performance report, a rank-tracker export, or aeo-audit probes — into a drift report: top gainers and losers per metric, growth/decline/reshuffle/stable/new/lost classification, and a four-gate quality scorecard.
Install / Use
npx skills add indranilbanerjee/digital-marketing-pro --skill seo-driftInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Data & AnalyticsSupported Platforms
Our assessment of seo-drift
seo-drift scores 87/100 on our quality scale, 309th of 516 Data & Analytics skills we index.
Its SKILL.md is 11 KB long, well organised into 14 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
It has 832 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated 26 days ago, so seo-drift is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
seo-drift compared with similar skills
All 4 of these similar skills score higher than seo-drift; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| seo-drift (this skill)by indranilbanerjee | 87 | 832 | 26d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 90.1k | 18d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 12d ago | SKILL.md |
Frequently asked questions
- How do I install seo-drift?
- Run
npx skills add indranilbanerjee/digital-marketing-pro --skill seo-drift. The install tabs above show the steps for each supported agent. - Which AI agents does seo-drift work with?
- It is written for Cline, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is seo-drift safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is seo-drift still maintained?
- The repository was last updated 26 days ago, so seo-drift is actively maintained.
Skill content
View source on GitHubname: seo-drift description: "Compare two SEO snapshots from the same source — GSC, the GSC AI Performance report, a rank-tracker export, or aeo-audit probes — into a drift report: top gainers and losers per metric, growth/decline/reshuffle/stable/new/lost classification, and a four-gate quality scorecard. Triggers on "/digital-marketing-pro:seo-drift", "compare this month's GSC export to last month's", "what moved after the core update", "did the content refresh work", "which queries lost AI Mode impressions". Runs scripts/seo_drift.py on two CSVs, reads the brand profile for noise thresholds, and branches findings to /digital-marketing-pro:seo-audit, /digital-marketing-pro:aeo-geo, or /digital-marketing-pro:content-engine." argument-hint: "<baseline.csv> <current.csv> [--noise 5]" user-invocable: true
/digital-marketing-pro:seo-drift
Purpose
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.
Context efficiency
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.
When to Use
- Monthly performance review — last month vs the month before
- Core Update triage — pre-update vs post-update + settling window (use 14+ days after rollout-complete)
- AI Mode citation tracking — quarter-over-quarter
aeo-auditoutputs to see which queries gained / lost AI Mode citations (Google AI Mode citation diff is a leading indicator for organic decline) - Content refresh attribution — before vs after a planned content update to attribute lift to the refresh vs other factors
- GSC AI Performance Report — month-over-month deltas on the new (3 Jun 2026) combined AI Overviews + AI Mode report
- Site migration audit — pre-migration baseline vs post-migration settling
Don't use for single-point-in-time analysis (use the source skill — seo-audit, aeo-audit, gsc-ai-performance).
Brand context (auto-applied)
- Read
~/.claude-marketing/brands/_active-brand.jsonfor the active slug, then load~/.claude-marketing/brands/{slug}/profile.json - If no brand exists: ask "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults
- Apply
skills/context-engine/industry-profiles.mdfor industry-specific noise thresholds (YMYL industries should use higher--noiseto filter out routine Quality Rater Guidelines volatility)
Inputs
| 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.
Process (10 steps, numbered-file output)
All outputs go to ${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{YYYY-MM-DD}/.
00-input.md— capture baseline date range, current date range, source (GSC / GSC AI / rank-tracker / aeo-audit), brand context01-baseline.csv— copy baseline export here (so the drift run is reproducible months later)02-current.csv— copy current export here03-drift-run.json— run the script:python "${CLAUDE_PLUGIN_ROOT}/scripts/seo_drift.py" \ --baseline "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/01-baseline.csv" \ --current "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/02-current.csv" \ --top 30 --noise 5 \ --out "${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/{date}/03-drift-run.json"04-quality-scorecard.md— readquality_scorecardfrom03-drift-run.json. Ifstatus: needs_review, diagnose:date_range_distinct: warn→ script couldn't auto-validate. Manually confirm in00-input.mdthat baseline and current cover non-overlapping windows.sample_size: fail→ either input has < 50 rows. Re-export without row limits.metric_compatibility: fail→ no numeric metrics in BOTH inputs. Column-name mismatch — re-export from the same source.no_lookup_collisions: fail→ duplicate keys in one input (e.g., same query × page row twice). Re-export with deduplication or use--join-onto add a distinguishing column.
05-biggest-gainers.md— narrative on the top 10 gainers across impressions / clicks / position. For each: hypothesis on cause (new content? backlinks gained? Core Update favoured E-E-A-T? Featured Snippet rotation?). Hand off candidates to/digital-marketing-pro:content-enginefor amplification.05-biggest-losers.md— narrative on the top 10 losers. For each: triage matrix —is_yMYL × had_recent_change × Core_Update_window→ action (refresh content / restore reverted change / wait for next algo cycle / accept and reallocate).06-ai-mode-shift.md(only if input source is GSC AI Performance Report) — queries that LOST AI Mode impressions are a leading indicator. Cross-reference with/digital-marketing-pro:aeo-auditto verify citation loss in synthetic probes.07-classification-distribution.md— counts table:- growth / decline / reshuffle / stable / new / lost
- If >40% in decline: likely Core Update or competitor catch-up. Run
/digital-marketing-pro:seo-auditfor diagnosis. - If >20% reshuffle: likely intent shift (AI Mode reweighting). Run
/digital-marketing-pro:aeo-geoto align with new intent patterns. - If >30% growth: find amplification opportunities. Run
/digital-marketing-pro:content-engineto brief follow-ups. - If >15% new: new SERP coverage — track and validate intent fit.
PLAN.md— single-page summary: stats + scorecard + top 5 actions ranked by impact × effort, with owner suggestions (SEO lead / content lead / dev team).
Output format
${CLAUDE_PLUGIN_DATA}/{brand}/seo/seo-drift/2026-06-04/
├── 00-input.md
├── 01-baseline.csv
├── 02-current.csv
├── 03-drift-run.json
├── 04-quality-scorecard.md
├── 05-biggest-gainers.md
├── 05-biggest-losers.md
├── 06-ai-mode-shift.md (only when input is GSC AI Performance Report)
├── 07-classification-distribution.md
└── PLAN.md
Quality scorecard (the four gates)
| Gate | What it checks | Why it matters | |---|---|---| | date_range_distinct | Baseline and current cover non-overlapping windows | Overlapping windows produce false-positive deltas — same data on both sides | | sample_size | Each input has ≥ 50 rows | Below this, drift is noise | | metric_compatibility | ≥ 1 numeric metric exists in both inputs | If columns differ (e.g., Ahrefs vs GSC), there's nothing to compare | | no_lookup_collisions | No duplicate keys within an input | Duplicates make the delta math ambiguous |
status: ready requires sample, metric compatibility, and no-collision gates pass (date-range-distinct is warn not fail — the script can't always autodetect dates).
Classification rules
Each row in the report falls into one bucket:
| Classification | Trigger | Interpretation | |---|---|---| | growth | ≥ 2 metrics moved up > noise%, no metric down > 10% | Clear win — investigate for amplification | | decline | ≥ 2 metrics moved down > noise%, no metric up > 10% | Clear loss — triage by YMYL × Core-Update-window | | reshuffle | Significant moves in opposite directions (e.g., impressions up, position down) | AI Mode signature — content is being shown more broadly but for slightly different intents | | stable | No metric moved more than noise% | No action | | new | Absent in baseline, present in current | New content or new SERP coverage — track | | lost | Present in baseline, absent in current | Content removed, deindexed, or fell out of tracking window |
Position is special: for position, lower numbers are better. The script automatically inverts position-delta direction for gain/loss ranking — you'll see -85.9% under position as a top gainer (page moved from position 12 to position 2).
Chain handoffs
This skill is typically a consumer + diagnostician:
/digital-marketing-pro:gsc-ai-performanceorseo-auditoraeo-audit— generates the snapshots/digital-marketing-pro:seo-drift— this skill- Branch by finding:
- High decline →
/digital-marketing-pro:seo-auditfor technical-side check +/digital-marketing-pro:content-decay-scanfor content-side - High reshuffle →
/digital-marketing-pro:aeo-geofor intent realignment - High growth →
/digital-marketing-pro:content-enginefor amplification briefs
- High decline →
Tips & caveats
- Don't run during a Core Update rollout. Wait until Google announces "rollout complete" + 7–14 days of settling. Mid-rollout deltas are unreliable.
- Position deltas are noisier than impression/click deltas — pages bouncing between positions 8 and 12 produce ±30% position deltas that mean nothing. Trust impression/click moves more for diagnosis.
- GSC's data lag is ~3 days. When pulling "current month" data, use the date range ending 3 days ago, not yesterday.
- The GSC AI Performance Report (3 Jun 2026) has NO click data. drift on AI report = impressions-only drift. Don't try to compute CTR drift from it.
- For Core Update triage, run drift twice: pre-update vs day-after-rollout-complete (the "blast"), and pre-update vs 14-days-after (the "settled state"). The two often disagree, and the 14-day view is the one that matters.
- Reshuffle classification is a leading indicator — when reshuffle counts spike, intent reweighting is happening. The next quarter's drift will usually show clearer growth/decline. Don't react too fast.
Agents used
analytics-analyst(primary) — interpretation + cause hypothesesseo-specialist— for technical-cause hypotheses on loserscompetitive-intel— when decline correlates with a competitor's winmarket-intelligence— for algo-update context (was there a Core Update in the window?)
See also
/digital-marketing-pro:gsc-ai-performance— pull the GSC AI Performance Report (input source)/digital-marketing-pro:seo-audit— diagnose decline causes/digital-marketing-pro:aeo-audit— diagnose AI Mode citation loss/digital-marketing-pro:content-decay-scan— for content-side decline triage/digital-marketing-pro:content-engine— for amplifying gainersscripts/seo_drift.py— the underlying drift engine
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
