apify-trend-analysis

Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.

Quality

48%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/apify-trend-analysis/SKILL.md

Quality

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 is helpful for differentiation. However, it lacks a 'Use when...' clause, which is critical for Claude to know when to select this skill, and the actions described are high-level rather than concrete. Adding explicit trigger guidance and more specific capabilities would significantly improve its effectiveness.

Suggestions

Add an explicit 'Use when...' clause with trigger terms like 'trending topics', 'what's trending', 'social media trends', 'viral content', 'hashtag analysis'.

List more specific concrete actions such as 'analyze trending hashtags, compare keyword popularity over time, identify viral content patterns, generate trend reports'.

Include common user phrasing variations like 'social media analytics', 'what's popular on TikTok/Instagram', or 'trend analysis' to improve trigger term 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, analyze hashtags).	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 since the 'when' is entirely absent, this scores at the lower end.	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', 'hashtags', 'social media analytics', or 'what's trending'.	2 / 3
Distinctiveness Conflict Risk	The combination of multiple specific social media platforms and trend tracking creates a somewhat distinct niche, but 'content strategy' is broad enough to overlap with general social media management or marketing skills. The lack of explicit trigger boundaries 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 checkpoints within the workflow (e.g., verifying schema fetch success before proceeding), the large inline Actor table that could benefit from extraction to a reference file, and boilerplate sections that waste tokens. The error handling exists but is disconnected from the workflow steps.

Suggestions

Add explicit validation checkpoints after Step 2 (verify schema was fetched successfully) and Step 4 (verify actor run succeeded before summarizing), integrating error handling as feedback loops within the workflow.

Extract the Actor lookup table to a separate reference file (e.g., ACTORS.md) and link to it from SKILL.md to improve progressive disclosure and reduce inline bulk.

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. Some explanatory text like 'This returns:' bullets are mildly redundant. Overall mostly efficient but has clear fat to trim.	2 / 3
Actionability	Provides fully executable bash commands for fetching schemas and running actors, concrete CLI flags, specific Actor IDs, and clear output format options. 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 lacks explicit 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 the error handling section is separate rather than integrated as feedback loops within the workflow.	2 / 3
Progressive Disclosure	References scripts at `${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js` but no bundle files are provided to verify. The large Actor lookup table could be extracted to a reference file. The skill is somewhat monolithic with the full table inline, though the overall section structure is reasonable.	2 / 3
	Total	9 / 12 Passed

Validation

90%

Warnings & errors only

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: 96e6849

Reviewed: 33 minutes ago

Table of Contents

Discovery Implementation Validation

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