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apify-trend-analysis

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

56

Quality

65%

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-trend-analysis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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.

The content is well-structured and actionable with concrete commands and a clear step sequence, but the workflow lacks an inline validation checkpoint before summarization (relevant for batch scraping), and the referenced run_actor.js script is not present in any bundle directory.

Suggestions

Insert an explicit validation step between Step 4 and Step 5 (e.g., "Verify the run succeeded and the output file exists before summarizing") to add a feedback loop for batch scraping.

Provide at least one fully filled, copy-paste-ready example command (real actor ID and a sample JSON input) to cover the common case and raise actionability.

Trim the generic "When to Use" and "Limitations" boilerplate to skill-specific guidance, and ship the referenced run_actor.js in a scripts/ bundle so the documented commands are executable.

DimensionReasoningScore

Conciseness

The body is mostly efficient — a compact prerequisites list, a focused actor-selection table, and direct bash commands with no over-explanation of concepts Claude already knows. Not 5 because the boilerplate "When to Use" and "Limitations" sections ("Use this skill when tackling tasks related to its primary domain...") are generic padding that could be trimmed.

4 / 5

Actionability

Provides concrete, mostly executable bash commands for schema fetch and three output modes (quick/CSV/JSON) with a real invoked script path. Not 5 because placeholders (ACTOR_ID, JSON_INPUT, YYYY-MM-DD_OUTPUT_FILE) prevent copy-paste readiness and no filled example is given for the common case.

4 / 5

Workflow Clarity

Five steps are clearly sequenced with a progress checklist, but there is no validation checkpoint (e.g., verify the run succeeded / output file exists before summarizing) inside the workflow; failures are only handled in a separate Error Handling section. Scraping many results is a batch operation, so per the feedback-loop cap workflow clarity cannot exceed 3.

3 / 5

Progressive Disclosure

Well-organized into clear sections (Prerequisites, Workflow, Steps, Error Handling) with a one-level reference to a run script and no nested references. Not 5 because the referenced script lives outside any provided bundle (no references/scripts/assets dirs exist) and the large inline actor table could arguably be a separate reference file.

4 / 5

Total

15

/

20

Passed

Description

61%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.

The description clearly states what the skill does and names concrete platforms, but omits any "Use when..." trigger guidance, which caps completeness at 3. Trigger-term and distinctiveness are solid thanks to the platform enumeration.

Suggestions

Add an explicit "Use when..." clause naming natural trigger phrases (e.g., "Use when the user wants to research trending topics, hashtags, or viral content across social platforms").

Broaden the action vocabulary beyond "Discover and track" to name more concrete actions (e.g., scrape, export, summarize trend metrics) for higher specificity.

Include synonyms or shorthand users say (e.g., "trending", "viral", "social listening") to push trigger-term coverage toward comprehensive.

DimensionReasoningScore

Specificity

Names the domain ("emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok") and 1-2 concrete actions ("Discover and track"), but the action set is not comprehensive — exactly the anchor 3 case. Not 4 because it lacks several distinct specific actions beyond discover/track.

3 / 5

Completeness

Has a clear "what" (discover and track trends across named platforms to inform content strategy) but no "Use when..." clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3. Not 4 because "when" is entirely missing rather than weakly present.

3 / 5

Trigger Term Quality

Includes natural terms users would say ("trends", "Google Trends", "Instagram", "Facebook", "YouTube", "TikTok", "content strategy") with good platform coverage. Not 5 because it lacks synonyms and explicit trigger phrasing, and not 3 because platform names are concrete, natural keywords rather than vague.

4 / 5

Distinctiveness Conflict Risk

Enumerating five specific platforms plus "trends"/"content strategy" gives it a mostly distinct niche with minor overlap risk against other analytics skills. Not 5 because the absence of explicit trigger phrases leaves some overlap ambiguity.

4 / 5

Total

14

/

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.

Validation15 / 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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