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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.

58

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./competitive-ads-extractor/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-organized and easy to navigate but padded with a large simulated example and redundant restatements, lacks any executable extraction method, and omits validation checkpoints for its batch-scraping workflows. It scores a uniform 2 across all content dimensions.

Suggestions

Replace the simulated "Example" process/output block with a real, executable extraction procedure (actual tooling, API calls, or script invocations) so guidance is copy-paste ready.

Add validation/feedback checkpoints to the batch workflows (e.g., verify screenshots saved, handle empty/failed ad-library responses, retry on rate limits).

Move the large example output and analysis frameworks into a separate reference file and keep SKILL.md a lean overview, restoring the token budget.

DimensionReasoningScore

Conciseness

Mostly organized but padded — the 110+ line simulated "Example" output block and redundant sections ("What You Can Learn" re-states "What This Skill Does", "Related Use Cases") could be tightened without losing operational value.

2 / 3

Actionability

Provides concrete prompt templates ("Extract all current ads from [Competitor]..."), but the extraction mechanism itself is only simulated ("Accessing Facebook Ad Library... Found: 23 active ads") with no real executable code, tooling, or method, leaving key details missing.

2 / 3

Workflow Clarity

Multi-step workflows ("Ad Campaign Planning", "Positioning Research") are clearly sequenced, but this batch-scraping operation has no validation checkpoints or error-recovery feedback loops, capping it at 2 per the batch-operation guideline.

2 / 3

Progressive Disclosure

Well-sectioned with clear headings, but it is a single ~290-line file with no bundle references; the large inline example output and analysis frameworks are reference material that should be split out, and the under-50-line carve-out does not apply.

2 / 3

Total

8

/

12

Passed

Description

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific and distinctive with good natural trigger terms, but lacks an explicit "Use when..." clause, which caps its completeness at 2. Adding an explicit trigger clause would raise it to a top-tier description.

Suggestions

Add an explicit "Use when..." clause naming natural triggers (e.g., "Use when researching competitor ad strategies, analyzing ad libraries, or seeking inspiration for ad copy").

Mention additional platform variants users might say (e.g., TikTok, Instagram, Google ads) to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Extracts and analyzes competitors' ads", understanding "messaging, problems, and creative approaches", and "Helps inspire and improve your own ad campaigns" — matching the multiple-specific-actions anchor.

3 / 3

Completeness

It clearly answers "what" (extract/analyze competitor ads) but provides no explicit "Use when..." trigger clause, so per the guideline a missing explicit trigger caps completeness at 2.

2 / 3

Trigger Term Quality

Covers natural terms users would say — "competitors' ads", "ad libraries (Facebook, LinkedIn, etc.)", "messaging", "creative approaches", "ad campaigns" — giving good natural-keyword coverage.

3 / 3

Distinctiveness Conflict Risk

Competitive ad-library extraction is a distinct niche with specific triggers (Facebook/LinkedIn ad libraries, competitor ads) that are unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Prat011/awesome-llm-skills
Reviewed

Table of Contents

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