AGENT SKILL

content-effort-audit

Score visible effort evidence on specified URLs. Use when the user asks for a Content Effort audit, rater-style effort scoring, low-effort AI content review, or whether a page would look Lowest under QRG §3.2. Distinct from library keep/refresh/prune (seo-aeo-content-strategy) and from on-page ski-ramp implementation (on-page-seo-aeo-optimization).

适用职业内容创作者
License 许可
MIT
最近更新
2026-09-16
Stars
★ 19
Forks
2

01 前言 Front Matter

name
content-effort-audit
description
Score visible effort evidence on specified URLs. Use when the user asks for a Content Effort audit, rater-style effort scoring, low-effort AI content review, or whether a page would look Lowest under QRG §3.2. Distinct from library keep/refresh/prune (seo-aeo-content-strategy) and from on-page ski-ramp implementation (on-page-seo-aeo-optimization).

02 资源文件 2

03 SKILL.md 正文

Content Effort Audit

Score visible effort on finished URLs. Production hours, cost, and process do not count unless they left residue a stranger can point at.

Why this matters

Google’s Search Quality Evaluator Guidelines judge Main Content quality by effort, originality, and talent or skill, plus accuracy on informational/YMYL pages. 2025 updates made “little to no effort, originality, and added value” a Lowest path, including AI paraphrase and scaled content abuse. Generative AI alone does not determine the rating.

Three evidence layers stay separate:

  1. QRG effort — documented rater criterion (primary source).
  2. Leaked contentEffort — reported LLM estimate for article pages. Mapping it to QRG is inference, not a Google statement.
  3. People-first questions — original information, first-hand expertise, not just rewriting sources.

Do not brief “Content Effort is a confirmed ranking factor.” Operate as if visible effort is industrially scored. Label the leak as speculation.

Cross-links: library keep/refresh/prune → seo-aeo-content-strategy. Implementing effort adds on the page → on-page-seo-aeo-optimization.

Process

  1. Classify page purpose. Recipe, calculator, review, explainer, clip, documentary — the bar is relative to purpose, not word count.
  2. Gather visible evidence only. First-party facts, original artifacts, synthesis, craft, curation choices, added value vs substitutes. Ignore time logs, “human review” checkboxes, and origin stories that are not on the URL.
  3. Score six signals, 0–2 each (0–12 total). Use references/vee-rubric.md. Do not invent Google’s weights.
  4. Map to QRG language. 0–3 Lowest-risk evidence, 4–6 Low, 7–9 High, 10–12 Highest-evidence. Then apply the purpose modifier.
  5. Recommend specific effort adds. A zero on first-party information is a measurement or primary document, not “write more.” See the rubric’s add column.
  6. Flag site-level scaled low-effort only after sampling 3+ URLs that share a skeleton. One thin URL is a page problem.
  7. Hand off implementation to on-page SEO/AEO for ski-ramp, titles, and schema. This skill stops at the effort verdict.

Output

Per URL:

Field Required
Purpose class Yes
Six-signal table (0–2) Yes
Total /12 and band Yes
QRG-aligned risk (Lowest / Low / High evidence) Yes
Missing-evidence list Yes
Prioritized effort adds Yes
Leak column labeled inference Yes
Scaled low-effort flag Optional, after 3+ URL sample

Worked pair: references/worked-examples.md.

Rules

  • Visible effort ≠ production effort.
  • Origin (human vs AI) ≠ rating.
  • Word count is not a signal.
  • Do not coin a fake “Google Content Effort score.”
  • Do not collapse this audit into E-E-A-T or keep/refresh/prune.

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