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competitive-ads-extractor

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

Install with Tessl CLI

npx tessl i github:davepoon/buildwithclaude --skill competitive-ads-extractor
What are skills?

51

1.22x

Quality

26%

Does it follow best practices?

Impact

97%

1.22x

Average score across 3 eval scenarios

Optimize this skill with Tessl

npx tessl skill review --optimize ./plugins/all-skills/skills/competitive-ads-extractor/SKILL.md
SKILL.md
Review
Evals

Evaluation results

93%

20%

ClearView CRM Competitive Ad Analysis

Analysis report structure and output formats

Criteria
Without context
With context

Analysis markdown file

100%

100%

Overview: total ad count

100%

100%

Overview: themes with percentages

25%

50%

Overview: format split

75%

100%

Overview: CTA patterns

100%

100%

Key Problems section

50%

100%

Key Problems: copy examples

62%

100%

Creative Patterns section

90%

100%

Copy section: headlines

75%

62%

Copy section: body patterns

100%

100%

Audience Targeting section

25%

100%

Recommendations section

80%

100%

CSV output

100%

100%

Without context: $0.2156 · 1m 30s · 10 turns · 15 in / 4,498 out tokens

With context: $0.5227 · 2m 18s · 22 turns · 439 in / 7,209 out tokens

100%

24%

First Paid Ad Campaign Planning for Focusly

Ad campaign planning workflow

Criteria
Without context
With context

Competitor patterns identified

70%

100%

Key problems highlighted

70%

100%

Messaging gaps identified

91%

100%

Unique angles brainstormed

83%

100%

Test ad variations drafted

93%

100%

Copy patterns documented

37%

100%

Audience segments mapped

87%

100%

CTA patterns noted

85%

100%

Recommendations section

40%

100%

CSV output

87%

100%

Without context: $0.3309 · 2m 5s · 15 turns · 22 in / 5,947 out tokens

With context: $0.6088 · 3m 3s · 23 turns · 29 in / 9,124 out tokens

100%

12%

Market Entry Positioning Strategy for GridHR

Competitive positioning research workflow

Criteria
Without context
With context

All competitors analyzed

100%

100%

Positioning mapped per competitor

100%

100%

Key problems per competitor

100%

100%

Audience segments per competitor

75%

100%

Cross-competitor common themes

90%

100%

Underserved angles identified

93%

100%

Differentiated messaging developed

100%

100%

CTA patterns across competitors

28%

100%

Recommendations section

80%

100%

Structured comparison output

80%

100%

Without context: $0.2702 · 1m 47s · 13 turns · 20 in / 5,195 out tokens

With context: $0.6138 · 2m 46s · 26 turns · 31 in / 8,284 out tokens

Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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