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apify-competitor-intelligence

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

81

2.66x
Quality

Does it follow best practices?

Impact

96%

2.66x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

80%

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

The body is actionable and lean, with executable commands and a useful Actor-selection table, but lacks an explicit validation checkpoint for its batch extraction runs and keeps a large reference table inline rather than offloading it. Adding a verify step and externalizing the Actor catalog would strengthen it.

Suggestions

Add an explicit validation checkpoint after Step 4 (e.g. verify the output file is non-empty and matches the requested format before summarizing) to satisfy the batch-operation feedback-loop requirement.

Move the 28-row Actor-selection table into a references file (e.g. references/actors.md) and link to it from Step 1, keeping the SKILL.md body a concise overview.

Bundle the referenced run_actor.js script under the skill's scripts/ directory and reference it via a verifiable relative path instead of ${CLAUDE_PLUGIN_ROOT}/reference/scripts/.

DimensionReasoningScore

Conciseness

Lean prose with no concept padding; the Actor-selection table is dense, non-obvious reference data where every row earns its place rather than explaining things Claude already knows.

3 / 3

Actionability

Provides copy-paste-ready executable commands (mcpc schema fetch, node --env-file run_actor.js with --actor/--input/--output/--format flags) with specific Actor IDs, matching the fully-executable anchor.

3 / 3

Workflow Clarity

A clear 5-step sequenced checklist with an error-handling section, but batch data-extraction runs have no explicit validation/verification checkpoint, capping clarity at 2 per the batch-operations guideline.

2 / 3

Progressive Disclosure

No bundle files are provided (references/scripts/assets absent), and the large inline Actor-selection table is content that could be split into a separate reference file; the only script reference points outside the bundle and cannot be verified.

2 / 3

Total

10

/

12

Passed

Description

67%

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, naming concrete analysis types and platforms, but lacks an explicit 'when to use' trigger clause and natural trigger-term coverage. Adding a 'Use when...' sentence with common phrasings would lift completeness and trigger quality.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when researching competitors, benchmarking rival content, pricing, or ads across Google Maps, Booking.com, Facebook, Instagram, YouTube, or TikTok.'

Include natural user phrasings such as 'competitor research', 'competitor benchmarking', or 'rival analysis' to improve trigger-term coverage.

Keep the third-person voice (already correct) but ensure the trigger clause names the situations users would describe, not just the platforms.

DimensionReasoningScore

Specificity

Lists multiple concrete analysis actions — 'competitor strategies, content, pricing, ads, and market positioning' — matching the anchor for comprehensive specific actions.

3 / 3

Completeness

Clearly states what the skill does but has no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 2 per the rubric guidelines.

2 / 3

Trigger Term Quality

Includes natural platform keywords (Google Maps, Booking.com, Facebook, Instagram, YouTube, TikTok) but misses common variations like 'competitor research' or 'benchmarking' and lacks trigger phrasing.

2 / 3

Distinctiveness Conflict Risk

The competitor-intelligence framing scoped to named platforms forms a clear niche unlikely to trigger for unrelated skills.

3 / 3

Total

10

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
sickn33/antigravity-awesome-skills
Reviewed

Table of Contents

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