apify-content-analytics
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
57
66%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/antigravity-awesome-skills-claude/skills/apify-content-analytics/SKILL.mdQuality
Discovery
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 strong in specificity and distinctiveness, clearly naming concrete actions and specific platforms that carve out a well-defined niche. However, it lacks an explicit 'Use when...' clause, which limits its completeness score, and could benefit from additional natural trigger terms that users commonly use when discussing social media analytics.
Suggestions
Add a 'Use when...' clause such as 'Use when the user asks about social media analytics, post performance, follower growth, or marketing campaign results.'
Include additional natural trigger terms like 'social media', 'likes', 'followers', 'views', 'impressions', 'reach', and 'social analytics' to improve keyword coverage.
| Dimension | Reasoning | Score |
|---|---|---|
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 |
Implementation
64%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 skill with strong actionability—concrete commands, a useful Actor mapping table, and clear output format options. Its main weaknesses are the lack of validation checkpoints in the workflow (especially important since it involves external API calls that can fail), and the inline verbosity of the large Actor table that could benefit from being in a separate reference file. The generic limitations section and some redundant framing add unnecessary tokens.
Suggestions
Add validation checkpoints after Step 2 (verify schema was fetched successfully) and Step 4 (verify Actor run completed and returned expected data), with explicit retry/fix guidance for failures.
Move the large Actor selection table to a separate reference file (e.g., ACTORS.md) and keep only a brief summary or top 3-4 most common use cases inline.
Remove the generic 'Limitations' boilerplate section—these are general Claude behaviors, not skill-specific constraints.
Integrate error handling into the relevant workflow steps rather than listing them separately at the end.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some unnecessary elements: the large Actor table could be more compact, the 'Limitations' section contains generic boilerplate that doesn't add value, and the 'When to Use' section partially restates the obvious. The checklist and workflow steps are mostly lean though. | 2 / 3 |
Actionability | Provides fully executable bash commands with clear placeholders, a comprehensive Actor selection table mapping user needs to specific Actor IDs, concrete output format options, and specific error messages with resolutions. Commands are copy-paste ready with appropriate variable substitution. | 3 / 3 |
Workflow Clarity | The 5-step workflow is clearly sequenced with a progress checklist, but lacks validation checkpoints. There's no step to verify the Actor schema was fetched correctly, no validation that the input JSON is well-formed before running, and no feedback loop for handling partial results or retrying failed runs. The error handling section is separate rather than integrated into the workflow. | 2 / 3 |
Progressive Disclosure | The content references scripts at `${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js` but no bundle files are provided to verify these exist. The Actor table is quite large and could be split into a reference file. The skill is structured with clear sections but keeps everything inline rather than appropriately splitting the lengthy reference table. | 2 / 3 |
Total | 9 / 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.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- sickn33/antigravity-awesome-skills
- Commit
b3869ba
- Reviewed
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