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    SEO Change Impact Checker: Did It Work or Is It Noise?

    2

    Unlike plain before/after GSC comparisons, this subtracts sitewide swings with a control group and tests your SEO change against 100+ placebo dates, then says REAL WIN, REAL LOSS, NOISE or TOO EARLY.

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    SEO Change Impact Checker: Did It Work or Is It Noise?

    SEO Change Impact Checker: Did It Work or Is It Noise?

    Example session with this skill installed

    Did the title rewrite on /guides/ (shipped 2026-08-17) work? Here's my GSC date+page export: gsc.csv

    python3 scripts/seo_change_impact.py --csv gsc.csv --change-date 2026-08-17 --treatment /guides/ --as-of 2026-10-27 --out impact-out

    • Read your context and instructions
    • Compiled the seo change impact

    (Real run on the bundled SYNTHETIC demo data)

    Change on 2026-08-17: REAL WIN

    Changed pages: +18% clicks (day-of-week adjusted) while the control pages moved -1%. Net effect +20%; normal week-to-week noise for this data is -7% to +8%. Driver: impressions +19% (net), avg position 9.0 -> 7.5. The lift is outside the noise band: keep the change and roll it out to similar pages.

    | Metric | Before | After |
    | Window | 2026-07-20 to 2026-08-16 | 2026-08-20 to 2026-09-16 (28 usable days) |
    | Clicks/day (DOW-adjusted) | 185.64 | 219.6 |
    | Avg position | 9.0 | 7.45 |

    • Treatment lift +18.3%, control lift -1.4%, net effect +20.0%
    • Noise band (90%): -6.8% to +8.5% via placebo test on 80 fake change dates in your own history

    Note: Ignored 2 most recent day(s): GSC data for the last ~3 days is incomplete.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Did your title rewrite, content refresh or internal-linking push actually work, or is it randomness? Plain before/after charts in Search Console fool people all the time: a core update, a holiday, a weekend-heavy window or the last 2-3 days of incomplete GSC data can fake a win or hide one.

    One command (stdlib Python 3.9+, no installs, no API keys) reads your Search Console data and the change date(s) and gives a verdict per change:

    • Matched windows of whole weeks before/after the change, with a 3-day recrawl buffer and day-of-week adjustment
    • Control group diff-in-diff: changed pages vs. all other (or chosen) pages, so sitewide drops and seasonality cancel out
    • Noise band from your own history: the same test is re-run on 100+ fake "change dates" where nothing happened (weekly-block bootstrap when history is short)
    • GSC data-lag guard: the last 3 days are dropped and a TOO EARLY verdict gives the exact re-run date
    • Drivers: impressions, average position and CTR before vs after, so you know why it moved
    • Warnings for overlapping changes, sitewide shifts, low volume and partial windows

    Output: report.md (plain English, client-ready) + result.json. Exit code 0/1/3 for automation.

    Demo on clearly labeled SYNTHETIC data (fake domain, planted ground truth): a planted +20% title-rewrite win comes out as REAL WIN net +20.0% (noise band -6.8% to +8.5%). A page group with no real change shows -9% in a naive before/after, but with the control it's NOISE because the whole site fell 12%. A change 7 days ago comes out TOO EARLY with a re-run date.

    Pairs with: Find Decaying Pages (what to refresh), Search Console Quick Wins (what to change) and GSC History Warehouse (keep the daily data this tool needs).

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Requires

    Python 3.9+
    Google Search Console export (CSV) or a saved Search Analytics API JSON file

    Listed2 days ago
    Updatedtoday

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