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Marketing · Version 1.0.0 · Reviewed 2026-08-02

Landing Page Claim Evidence Auditor

Make claim-to-evidence mapping and message specificity review with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Reviews every landing-page claim for specificity, evidence, audience relevance, differentiation, and the risk of sounding impressive without being provable.

₹299 one-time

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What this skill helps you do

  • Claim-to-evidence mapping
  • Message specificity review
  • Proof gap detection

How Landing Page Claim Evidence Auditor works

You provide

Draft assets, audience evidence, and the claim under review

It inspects

Substantiation and differentiation for claim-to-evidence mapping

It decides

A message specificity review revision with claims tied to evidence

You verify

A measurement plan defined before the asset ships

What it checks first

Landing Page Claim Evidence Auditor reviews every landing-page claim for specificity, evidence, audience relevance, differentiation, and the risk of sounding impressive without being provable. Use it when the work involves Claim-to-evidence mapping, Message specificity review, Proof gap detection.

  1. Whether a claim is substantiated by evidence a buyer could independently verify.
  2. Whether the differentiation is real or something every competitor also asserts.
  3. Whether the message describes the customer problem or the product feature list.
  4. Sample quality behind any audience insight, since a few loud accounts are not a segment.

Failure modes it recognizes

  • Positioning built on claims competitors make identically, which produces no differentiation at all.
  • A feature list presented as a value proposition, forcing the buyer to do the translation.
  • Optimizing one funnel stage in isolation and moving the bottleneck without net gain.
  • Attributing conversion to messaging when the segment already arrived with intent.

Answers it will reject

  • Superlatives without substantiation, which reduce credibility rather than increase it.
  • Reporting aggregate conversion across mixed segments, hiding that one is failing badly.
  • Copying competitor language, which concedes their framing of the category.

Decision rules it applies

  • Keep only claims that are true, specific, and hard for a competitor to assert.
  • State the evidence and its strength behind every audience assertion.
  • Define the measurement and review date before the asset ships.

Evidence it asks for

  • Quote the source evidence beside each claim so it can be audited.
  • Report counts with denominators rather than percentages alone.
  • Define the leading indicator that will move before the lagging metric does.

The method inside

  1. Start from audience evidence and the behavior to change
  2. Map each message to a problem, outcome, and proof
  3. Remove claims that are vague, duplicated, or unsupported
  4. Define the measurement and approval criteria before publication

Deliverables

  • Claim-to-evidence mapping evidence map
  • Message specificity review revision brief
  • Proof gap detection measurement checklist

Evidence requirements

  • Approved claims and supporting research
  • Specific audience, buying situation, and desired behavior
  • Customer language, campaign brief, or content source material

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Audit this landing page and mark every claim that is vague, unsupported, or indistinguishable from competitors.

Expected output

“Transform your workflow” has no measurable outcome or proof. The strongest defensible claim is 42% faster review completion, but its methodology needs a visible footnote before publication...

Boundaries and compatibility

Ideal for

  • Claim-to-evidence mapping: produce a decision or artifact grounded in supplied evidence.
  • Message specificity review: produce a decision or artifact grounded in supplied evidence.
  • Proof gap detection: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Fabricating testimonials, statistics, or competitive claims
  • Presenting correlation as causal proof

Agent compatibility

  • GitHub Copilot Agent Skills
  • Cursor Agent Skills
  • Claude Code Skills
  • OpenAI Codex Skills
  • JetBrains Junie Skills

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.