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@93b720e
by Agrici.Danielagricidaniel/claude-seo18k stars
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FLOW framework integration: evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.

Use this Skill: https://skilld.dev/gh/agricidaniel/claude-seo/seo-flow

This session only. Nothing lands on disk.

referencespromptswindual-surface-content-scorecard.md

≈534 tokens on demand. Your agent reads this file only when SKILL.md points to it.

<!-- Source: github.com/AgriciDaniel/flow | License: CC BY 4.0 | Synced: 2026-04-26 -->

title: "Dual-Surface Content Scorecard" description: "Dual-Surface Content Scorecard" updated: 2026-04-25 tags:

  • prompts
  • win

Dual-Surface Content Scorecard

Use This When

Use this when you need to judge whether a page can perform in traditional search and AI-assisted discovery while still supporting conversion.

AI Compatibility

Claude, GPT, Gemini, and other long-context models. Works best with current customer language and conversion evidence.

Inputs

  • Page copy.
  • Target queries or topics.
  • Intended conversion goal.
  • Audience segment.
  • Known first-party insights.
  • Performance data, if available.
  • Competing page examples, optional.

Prompt

Score this content for two discovery surfaces: traditional search and AI-assisted answer environments.

Evaluate:
1. Original usefulness and specificity.
2. Alignment with audience needs and decision stage.
3. Evidence, examples, data, or firsthand insight.
4. Clear answers to buyer questions.
5. Conversion support: CTA, proof, objection handling, and next step.
6. Refresh or update need.
7. Measurement readiness: traffic, engagement, qualified leads, sales conversions, and ROI indicators.

Return traditional search score, AI-assisted discovery score, conversion-readiness score, evidence strengths, gaps, risks, recommended updates, and the highest-impact next three actions. Use business-impact language, not traffic-only language.

Output

  • A structured Win-stage working document.
  • Prioritized recommendations.
  • Evidence and measurement gaps.
  • Claims or assumptions that require verification.

Example

Input: existing service page with traffic but low form submissions. Output: scores showing whether the page lacks buyer proof, direct answers, customer language, CTA clarity, or measurable conversion paths.

See Also

Source Note

Derived from SEJ State of SEO 2026, verified AI-search evidence, and SEJ B2B Lead Generation.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub1d

    The skill is a comprehensive SEO framework that uses structured prompts for analysis. It includes a synchronization feature to update its knowledge base from the author's GitHub repository. A low-risk surface for indirect prompt injection exists where user-provided URLs or topics are processed by AI models without explicit sanitization, though the prompts include instructions to limit output to provided evidence.

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  • Snyk1d

    Risk: LOW · No issues

Signed by skilld at 93b720e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 3 days ago
user-invocable
true
argument-hint
[stage] [url|topic]
metadata
{
  "author": "AgriciDaniel",
  "version": "2.4.1",
  "category": "seo"
}

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