Documents

Rank Tracker

Track keyword, SERP feature, competitor, and AI visibility changes against a cited baseline.

What it does

Track keyword positions, SERP feature ownership, competitor movement, and AI visibility against prior baselines. Rankings can come from connected tools, exports, or user-provided positions; every metric is tagged as Measured, User-provided, Estimated, or N/A. The output is a ranking report or delta summary covering movers, likely causes, recovery ideas, and next actions.

When to use it

  • Weekly keyword position review
  • SERP feature ownership audit
  • Competitor ranking comparison
  • AI citation visibility check

The skill document

Rank Tracker

Tracks keyword positions, SERP feature ownership, and AI visibility over time.

Quick Start

Set up rank tracking for [domain] targeting these keywords: [keyword list]
Analyze ranking changes for [domain] over the past [time period]

Skill Contract

Expected output: a ranking report or delta summary plus the standard handoff summary for memory/monitoring/.

  • Reads: current rankings, prior baselines, target keyword list, market/device, and any user-provided or tool metrics.
  • Writes: a user-facing monitoring deliverable and reusable summary.
  • Promotes: significant changes, confirmed anomalies, follow-up actions, and pending decisions to memory/open-loops.md.
  • Done when: every tracked keyword shows current position vs baseline with a labeled delta (or N/A); each position cites its source (tool export / user-provided / estimated); and biggest movers and likely causes are named.
  • Primary next skill: performance-monitor when recurring monitoring should become automated.

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

All integrations optional (see CONNECTORS.md). With tools, pull rankings from ~~SEO tool, impressions from ~~search console, traffic from ~~analytics, and AI citations from ~~AI monitor. Without tools, ask for positions, volumes, competitor data, and SERP feature status.

Zero-dependency measurement loop (no paid tool needed): never narrate a ranking movement you did not measure — record each check as a snapshot and let the ledger compute the delta. python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/ledger.py" record --source rank --data '{"": , ...}', then ledger.py diff --source rank for the change since the last check and ledger.py trend --source rank --field "" for the series. Record real Search Console positions when connected, or the positions the user provides at Tier 1. A ranking delta is a week-scale, confounded outcome — attribute it against a control (a holdout keyword/competitor), not against zero; see references/measurement-protocol.md. See scripts/connectors/README.md.

Decision Gates

Stop and ask the user when:

  • No target keywords are provided and none can be inferred from CLAUDE.md or prior monitoring records — offer: (1) supply a keyword list, (2) track the domain's top known terms, (3) cancel.

Continue silently (never stop for):

  • No prior baseline exists — record the current run as the baseline, label all positions as the first snapshot, and proceed (do not invent a "previous" position).
  • Missing optional tool data (SERP features, AI citations) — mark N/A and proceed.

Instructions

When a user requests rank tracking or analysis:

  1. Set Up Keyword Tracking — configure domain, market, device, language, update frequency, priorities, and competitor watchlist.
  2. Record Current Rankings — output a position table where every row cites its source (tool export / user-provided / estimated), with position ranges, ranking URLs, feature ownership, and movement vs baseline.
  3. Analyze Ranking Changes — highlight biggest wins, declines, stable terms, new rankings, lost rankings, likely causes, and recovery ideas; each delta labeled against its baseline.
  4. Track SERP Features — compare ownership of snippets, PAA, image/video packs, local packs, and related feature shifts.
  5. Track GEO / AI Visibility — monitor AI Overview presence, citation rate, citation position, and trend; mark each value Measured (from an ~~AI monitor) or N/A if unobserved.
  6. Compare Against Competitors — report share of voice, head-to-head comparisons, and threat levels.
  7. Generate Ranking Report — output overall trend, key wins, concerns, opportunities, SERP feature changes, GEO visibility, and recommendations, with each metric carrying its source tag.

Label every metric Measured (tool/export), User-provided, or Estimated (model inference); never present an estimate as measured; if a required metric is unavailable, mark it N/A — do not invent it.

Reference: See Ranking Analysis Templates for the complete output templates for all seven steps.

Example

A ranking report names the biggest winners, biggest drops, and next actions, with each position carrying its source tag and labeled delta against baseline.

Rank Change Quick Reference

Response Protocol

ChangeTimeframeAction
Drop 1-3 positionsWait 1-2 weeksMonitor — may be normal fluctuation
Drop 3-5 positionsInvestigate within 1 weekCheck technical issues and competitor changes
Drop 5-10 positionsInvestigate immediatelyRun a full diagnostic: technical, content, links
Drop off page 1Emergency responseComprehensive audit + recovery plan
Position gainedDocument and learnIdentify what worked and replicate

Reference: See Tracking Setup Guide for tracking setup, root-cause taxonomy, CTR benchmarks, SERP feature impact, and algorithm-update assessment.

Save Results

Ask "Save these results?" If yes, write to memory/monitoring/ — see Skill Contract §Save Results Template.

Reference Materials

  • Tracking Setup Guide — Setup rules, feature tracking, and interpretation guidance

Next Best Skill

Initial setup (no baseline) → performance-monitor. Subsequent runs (baseline exists) → Terminal. Visited-set rule applies per skill-contract.md.

Questions people ask

What happens if I do not have a previous ranking baseline?
The current run is recorded as the first snapshot. Positions are labeled accordingly, and no previous rankings or deltas are invented.
Can it work without paid SEO tools?
Yes. It can use positions, volumes, competitor data, and SERP feature status that you provide, then record snapshots and compute changes between checks.
How does it handle AI Overview and citation visibility?
It monitors AI Overview presence, citation rate, citation position, and trends when observed through an AI monitor. Unobserved values are marked N/A rather than inferred as measured.

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