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apify-content-analytics

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

62

Quality

74%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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

Quality

Content

82%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.

A well-executed operational skill: concrete commands for every path (quick answer, CSV, JSON), a tracked multi-step workflow with an actor-selection table, and thorough error handling. The only refinements are tightening minor redundancy and integrating validation checkpoints directly into the workflow steps.

DimensionReasoningScore

Conciseness

The body is lean with a dense, information-rich actor-selection table and no explanations of concepts Claude already knows; minor trimming is possible in the "(No need to check it upfront)" aside and the three near-duplicate run-command blocks that differ only in output flags.

4 / 5

Actionability

Fully executable, copy-paste-ready commands throughout: the mcpc schema-fetch pipeline with exact flags, node --env-file invocations for all three output modes with clearly marked ACTOR_ID/JSON_INPUT placeholders, and a specific error-to-fix table covering the common failure cases.

5 / 5

Workflow Clarity

A copy-and-track 5-step checklist gives a clear sequence with a user-preference checkpoint (Step 3) and error-recovery feedback loops in the Error Handling section; it stops short of 5 because validation/retry guidance lives in a separate section rather than as explicit inline checkpoints within the workflow steps.

4 / 5

Progressive Disclosure

Well-organized sections with the actor-decision table appropriately inline and a single clearly-signaled one-level-deep reference to the run_actor.js script; no bundle directories (references/, scripts/, assets/) exist alongside the skill to verify or further split content, so structure is good but not a full overview-plus-references layout.

4 / 5

Total

17

/

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.

A concise, action-oriented description with strong natural trigger terms and a well-scoped platform niche. Its main weakness is the absence of an explicit "Use when..." clause, which caps completeness at 3 and leaves the trigger guidance implicit.

Suggestions

Append a trigger clause, e.g. "Use when the user needs engagement, ROI, or content-performance metrics for Instagram, Facebook, YouTube, or TikTok posts, reels, videos, ads, or hashtags."

Add common synonyms users naturally say, such as "social media analytics", "views", "likes", or "follower growth", to broaden keyword coverage.

Mention the Apify Actor mechanism or export formats (CSV/JSON) in the description to sharpen the "what" and further distinguish it from built-in platform analytics.

DimensionReasoningScore

Specificity

"Track engagement metrics", "measure campaign ROI", and "analyze content performance" are three concrete actions scoped to four named platforms, matching the several-specific-actions anchor; it falls short of 5 because the objects remain generic (no named metrics like views/likes/followers or actions like exporting or scheduling).

4 / 5

Completeness

The "what" is clear (track engagement, measure ROI, analyze performance across four platforms), but there is no "Use when..." clause or equivalent explicit trigger guidance, which per the judging guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Natural phrases users would say are present ("engagement metrics", "campaign ROI", "Instagram", "Facebook", "YouTube", "TikTok"), but common variations like "analytics", "social media", and specific metric names (views, likes, followers) are missing, fitting the good-but-incomplete anchor rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

The four platform names carve out a mostly distinct niche with minor overlap risk against generic social-media or analytics skills; it is not 5 because the description omits the Apify/Actor mechanism that would fully differentiate it from native-platform analytics 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.

Validation — 15 / 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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