apify-trend-analysis
Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.
57
48%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/apify-trend-analysis/SKILL.mdQuality
Discovery
32%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 identifies a clear domain (social media trend tracking) and names specific platforms, which provides reasonable distinctiveness. However, it lacks a 'Use when...' clause, which significantly hurts completeness, and the actions described are high-level rather than concrete. Adding explicit trigger conditions and more specific capabilities would substantially improve this description.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about trending topics, viral content, social media trends, or wants to research what's popular on social platforms.'
Make capabilities more concrete by specifying actions like 'analyze keyword popularity over time, compare trend volumes across platforms, identify rising hashtags, and generate trend reports.'
Include natural user trigger terms like 'trending', 'viral', 'what's popular', 'hashtag trends', 'social media analytics' to improve keyword coverage.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (trend tracking) and lists specific platforms (Google Trends, Instagram, Facebook, YouTube, TikTok), but the actions are somewhat vague — 'discover and track emerging trends' and 'inform content strategy' lack concrete specifics about what operations are performed (e.g., generate reports, compare keywords, export data). | 2 / 3 |
Completeness | Describes what the skill does (discover and track trends across platforms) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'when' is not even implied strongly enough to warrant a 2. | 1 / 3 |
Trigger Term Quality | Includes good platform-specific keywords (Google Trends, Instagram, Facebook, YouTube, TikTok) and relevant terms like 'emerging trends' and 'content strategy', but misses common user variations like 'trending topics', 'viral', 'social media trends', 'what's popular', or 'hashtag analysis'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of multiple specific social media platforms and trend tracking creates some distinctiveness, but 'content strategy' is broad enough to overlap with general social media management or content planning skills. The lack of explicit triggers increases conflict risk. | 2 / 3 |
Total | 7 / 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 skill provides solid actionable guidance with executable commands and a clear multi-platform trend analysis workflow. Its main weaknesses are the lack of validation/feedback loops in the workflow (e.g., verifying Actor run success before proceeding) and the large inline Actor table that could benefit from being extracted to a reference file. The boilerplate sections at the end add no value and waste tokens.
Suggestions
Add a validation step after Step 4 to check if the Actor run succeeded before proceeding to summarization, and include a retry/fix loop for failed runs.
Move the Actor lookup table to a separate reference file (e.g., ACTORS.md) and link to it from the main skill to improve progressive disclosure.
Remove the generic 'When to Use' and 'Limitations' boilerplate sections — they add no skill-specific value and waste tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The large Actor table is useful reference but could be more compact. The boilerplate 'When to Use' and 'Limitations' sections add no value. The workflow is mostly efficient but has some padding (e.g., 'Based on character of use case' is vague filler). | 2 / 3 |
Actionability | Provides fully executable bash commands for fetching schemas, running actors in multiple output formats, and clear error handling with specific solutions. The commands are copy-paste ready with clear placeholder 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 ran successfully before summarizing, no feedback loop for retrying failed runs, and no validation of the JSON input before execution. | 2 / 3 |
Progressive Disclosure | References external scripts (run_actor.js) appropriately, but the massive Actor lookup table could be split into a separate reference file. The skill is somewhat monolithic with all content inline rather than linking to detailed Actor documentation or examples. | 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
b938655
- Reviewed
Table of Contents
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