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apify-content-analytics

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

58

Quality

67%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/apify-content-analytics/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%Weight 40%Scale 1-5

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-structured and actionable with concrete commands and a useful actor-mapping table, but the batch workflow lacks an explicit validation checkpoint before execution, and a small amount of redundancy with the description slightly reduces conciseness.

Suggestions

Insert a validation checkpoint between Step 2 and Step 4 (e.g., 'Verify required input parameters against the fetched schema before running') to lift workflow_clarity above the batch cap of 3.

Remove the redundant intro line under the '# Content Analytics' heading since it restates the frontmatter description.

Provide one fully concrete example input (a populated --input JSON for a common actor) to move actionability toward copy-paste-ready 5.

DimensionReasoningScore

Conciseness

An efficient actor-selection table and concrete commands respect the token budget, though the opening line ('Track and analyze content performance using Apify Actors...') duplicates the frontmatter description and could be trimmed.

4 / 5

Actionability

Provides executable bash commands with specific actor IDs and three output formats, but placeholders like ACTOR_ID and JSON_INPUT require user substitution, leaving minor gaps versus copy-paste-ready 5-anchor coverage.

4 / 5

Workflow Clarity

A clear 5-step sequence with a progress checklist exists, but this batch data-collection workflow has no validation checkpoint between fetching the Actor schema (Step 2) and running the script (Step 4), capping workflow clarity at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

Well-organized into clearly headed sections with a clearly signaled script reference (${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js); the 17-row actor table is large but appropriately serves discovery, leaving only minor organization gaps.

4 / 5

Total

15

/

20

Passed

Description

66%Weight 40%Scale 1-5

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 concretely states what the skill does and across which platforms, with strong natural trigger terms, but omits an explicit 'Use when...' trigger clause that would raise completeness and distinctiveness.

Suggestions

Append an explicit 'Use when...' clause (e.g., 'Use when the user needs cross-platform engagement, growth, or ROI metrics for social content') to lift completeness from 3 to 4-5.

Add common synonyms/variations (e.g., 'social media analytics', 'post performance', 'reel/video metrics') to broaden trigger-term coverage.

Tighten the verbs (e.g., 'scrape', 'export', 'compare') to push specificity toward 5.

DimensionReasoningScore

Specificity

Lists three concrete actions ('Track engagement metrics, measure campaign ROI, and analyze content performance') across four named platforms, but the verbs are slightly more generic than the 5-anchor's granular action list.

4 / 5

Completeness

The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, so completeness is capped at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Natural user-facing terms ('engagement metrics', 'campaign ROI', 'content performance', 'Instagram, Facebook, YouTube, and TikTok') are present, but synonym and variation coverage is incomplete versus the 5-anchor.

4 / 5

Distinctiveness Conflict Risk

Multi-platform social content analytics is a clear niche with distinct triggers, though minor overlap risk remains with broader social-media scraping skills.

4 / 5

Total

15

/

20

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/agentic-awesome-skills
Reviewed

Table of Contents

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