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@93b720e
by Agrici.Danielagricidaniel/claude-seo18k stars
2,665

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.

referencespromptswinconversion-audit-prompt.md

≈551 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: "Conversion Audit Prompt" description: "Conversion Audit Prompt" updated: 2026-04-25 tags:

  • prompts
  • win

Conversion Audit Prompt

Use This When

Use this when a page, campaign, or funnel gets traffic but produces weak leads, low conversion rate, unclear attribution, or poor sales follow-up quality.

AI Compatibility

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

Inputs

  • Page or funnel copy.
  • Traffic sources.
  • Conversion goal.
  • Analytics or conversion data.
  • Call, chat, or form transcript samples.
  • Known objections.
  • Ad copy or campaign promise.
  • Sales feedback, if available.

Prompt

Audit this conversion path for lead quality, friction, and measurement gaps.

Use the supplied page, campaign, and first-party conversation data. Identify:
1. Where visitor expectations may not match the page or offer.
2. Common objections and hesitation points.
3. Missing decision-making information.
4. Language mismatches between customers and the page.
5. CTA friction.
6. Tracking gaps across form, phone, chat, and offline outcomes.
7. Whether reporting connects to qualified leads or sales, not only traffic.

Return an executive summary, top blockers, lead-quality risks, messaging fixes, page/content fixes, tracking fixes, first-party data to collect next, and a ranked test backlog. Do not recommend more spend until content, offer clarity, and measurement gaps are assessed.

Output

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

Example

Input: paid search landing page with many calls but few booked appointments. Output: an audit of pricing clarity, qualification, phone attribution, repeated objections, CTA mismatch, and test priorities.

See Also

Source Note

Derived from PPC Trends 2026, CallRail/SEJ Better Leads More Sales 2025, and SEJ State of SEO 2026.

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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