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apify-content-analytics

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

57

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/apify-content-analytics/SKILL.md

The canonical home for this skill is apify-content-analytics in sickn33/antigravity-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

64%Scale 1-3

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

This is a functional, actionable skill with concrete executable commands and a clear multi-step workflow. Its main weaknesses are the large inline Actor lookup table that should be extracted to a reference file, and the lack of validation/feedback loops between workflow steps (e.g., checking if the actor run succeeded before summarizing). The error handling section is useful but would be more effective if integrated into the workflow.

Suggestions

Move the Actor lookup table to a separate reference file (e.g., ACTORS.md) and link to it from the main skill, keeping only 2-3 common examples inline.

Add a validation checkpoint after Step 4 (e.g., check exit code or output file existence) before proceeding to Step 5, and integrate error handling into the workflow as a feedback loop.

Add a brief verification step after the mcpc schema fetch in Step 2 to confirm the schema was retrieved successfully before proceeding.

DimensionReasoningScore

Conciseness

The large Actor lookup table is useful reference material but makes the skill quite long. Some sections like 'Ask User Preferences' and 'Summarize Findings' contain guidance Claude could infer. The table could be moved to a reference file.

2 / 3

Actionability

Provides fully executable bash commands for fetching schemas, running actors in multiple output formats, and clear CLI syntax with flags. The commands are copy-paste ready with clear placeholder substitution patterns.

3 / 3

Workflow Clarity

The 5-step workflow is clearly sequenced with a progress checklist, but there are no validation checkpoints between steps. After running the actor (Step 4), there's no verification that the run succeeded before proceeding to summarize. Error handling is listed separately but not integrated into the workflow as feedback loops.

2 / 3

Progressive Disclosure

The skill is somewhat monolithic — the 17-row Actor lookup table should be in a separate reference file. The skill references external scripts appropriately but doesn't split its own content. A quick-start section followed by references to detailed tables would improve navigation.

2 / 3

Total

9

/

12

Passed

Description

67%Scale 1-3

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 strong in specificity and distinctiveness, clearly naming concrete actions and specific social media platforms. However, it lacks an explicit 'Use when...' clause, which is critical for Claude to know when to select this skill, and it could benefit from more natural trigger terms that users would commonly say (e.g., 'social media analytics', 'followers', 'likes').

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about social media analytics, post performance, or marketing campaign results.'

Include more natural trigger terms users would say, such as 'social media', 'likes', 'followers', 'views', 'impressions', 'social media analytics', or 'marketing analytics'.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Track engagement metrics', 'measure campaign ROI', and 'analyze content performance', along with specific platforms (Instagram, Facebook, YouTube, TikTok).

3 / 3

Completeness

Clearly answers 'what does this do' with specific actions and platforms, but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric.

2 / 3

Trigger Term Quality

Includes good platform names and terms like 'engagement metrics', 'campaign ROI', and 'content performance', but misses common user variations like 'social media analytics', 'likes', 'followers', 'views', 'social media', or 'posts'.

2 / 3

Distinctiveness Conflict Risk

The combination of social media platforms (Instagram, Facebook, YouTube, TikTok) with engagement/ROI/performance analysis creates a clear niche that is unlikely to conflict with other skills like general analytics or non-social-media marketing tools.

3 / 3

Total

10

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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