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content-decay-predictor

读取 Google Search Console 的 page×date 点击与展现数据，按周聚合成各 URL 时间序列；用 Theil–Sen 趋势与去季节性处理区分持续衰减与短期波动，标记拐点，按斜率外推预测额外点击损失，并据此输出按可恢复损失排序的刷新优先级 JSON。

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最近更新 2026-10-18 21:41:10
分类：营销依赖：代码执行 / 读写文件 / 第三方 API应用场景：市场分析 / 报告撰写 / 数据处理 / 推荐

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add seoskills.sh/content-decay-predictor
Metadata
name
content-decay-predictor
description
Builds per-URL clicks and impressions time-series from Search Console, fits a trend to detect sustained decline and inflection points, and predicts which pages will keep decaying ranked by projected click loss. Use when the user asks which content to refresh, what pages are losing traffic, or wants a proactive content-refresh queue.
metadata
{"title":"Content Decay Predictor","category":"content"}

Content Decay Predictor

AGENT ROLE: Autonomous content-decay agent. Model each URL's organic trajectory, classify decay, project future loss, and emit the JSON in references/output.schema.json. Distinguish genuine sustained decay from seasonality and one-off dips.

OBJECTIVE

Identify URLs on a sustained downward organic trajectory, estimate how much more traffic they will lose if untouched, and rank them so refresh effort targets the biggest recoverable losses.

INPUTS

  • site_url (REQUIRED): verified GSC property.
  • lookback_weeks (OPTIONAL, default 26): history window (needs ≥ 12 for a stable trend).
  • min_baseline_clicks (OPTIONAL, default 20): weekly-clicks floor at peak to consider a URL worth analyzing.
  • horizon_weeks (OPTIONAL, default 8): projection horizon.

AUTHENTICATION (Search Console API)

  1. REQUIRE GOOGLE_APPLICATION_CREDENTIALS (SA) OR OAuth, scope https://www.googleapis.com/auth/webmasters.readonly.
    • IF absent THEN STOP error.code="AUTH_MISSING_CREDENTIALS".
  2. Verified user on site_url. IF 403 THEN STOP error.code="AUTH_NO_SITE_ACCESS".
  3. Endpoint: searchAnalytics/query with dimensions=["page","date"], weekly-aggregated client-side.

EXPECTED TOOL CALLS

  • Run scripts/decay.py --site {site_url} --weeks 26.
  • Fetch daily page×date clicks/impressions for the window (paged), aggregate to weekly per URL.

PROCEDURE (deterministic, per URL)

STEP 1 — BUILD the weekly clicks series over lookback_weeks. STEP 2 — QUALIFY: skip URLs whose peak weekly clicks < min_baseline_clicks (too small to matter) → skipped. STEP 3 — DESEASONALIZE: subtract a 4-week trailing seasonal component (or use a robust trend via Theil–Sen slope, which resists outliers). STEP 4 — CLASSIFY:

  • peak_to_recent = mean(last 4 weeks) / max(rolling 4-week mean).
  • decaying IF Theil–Sen slope < 0 AND peak_to_recent <= 0.7 (lost ≥30% from peak) sustained ≥ 4 weeks.
  • inflection_week = the week the sustained decline began. STEP 5 — PROJECT: extend the slope horizon_weeks forward (floored at 0); projected_additional_loss = current_weekly − projected_weekly_at_horizon, summed over the horizon. STEP 6 — SCORE refresh_priority = projected_additional_loss (biggest recoverable loss first); EMIT decaying URLs sorted desc.

RATE LIMITS & ERROR HANDLING

  • GSC 429/RESOURCE_EXHAUSTED → backoff 2^attempt (max 5) then STOP error.code="RATE_LIMITED".
  • Only final dataState rows; exclude the trailing incomplete week.
  • Large sites: cap analyzed URLs at the top 2000 by total clicks; note truncated=true.

MISSING / INSUFFICIENT DATA

  • IF a URL has < 12 weeks of data THEN mark insufficient_history and exclude from decay classification (cannot separate decay from noise).
  • Seasonality guard: a decline that matches a prior-year same-season dip is flagged seasonal_suspected=true, not decaying, when multi-year data exists; otherwise note the caveat.
  • Never predict negative traffic; floor projections at 0.

OUTPUT

One JSON object per references/output.schema.json. No prose.

FILES

  • scripts/decay.py — GSC weekly series, Theil–Sen trend, decay classification + projection.
  • references/output.schema.json — output contract.