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apify-audience-analysis

Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

46

Quality

48%

Does it follow best practices?

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Adds up to 20 points to the overall score

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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-audience-analysis/SKILL.md

The canonical home for this skill is apify-audience-analysis in sickn33/agentic-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 commands and a clear multi-step workflow. Its main weaknesses are the large inline Actor lookup table that could benefit from being in a separate reference file, and the lack of validation checkpoints within the workflow (e.g., verifying schema fetch success before proceeding, validating input JSON). The error handling section is useful but disconnected from the workflow steps.

Suggestions

Move the 18-row Actor lookup table to a separate reference file (e.g., ACTORS.md) and link to it from the main skill to improve conciseness and progressive disclosure.

Add explicit validation checkpoints in the workflow, e.g., after Step 2 verify the schema was fetched successfully before proceeding, and after Step 4 check the run status before summarizing.

Integrate error handling into the workflow steps rather than listing it separately, so Claude knows when to expect and handle each error type.

DimensionReasoningScore

Conciseness

The large Actor lookup table is useful reference material but makes the skill quite long. Some sections like 'Ask User Preferences' and the triple output format examples could be tightened. However, it doesn't over-explain concepts Claude already knows.

2 / 3

Actionability

Provides fully executable bash commands for fetching schemas and running actors, with concrete command-line flags and format options. The Actor ID table gives specific, copy-paste-ready identifiers for each use case.

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 schema was fetched correctly, no validation that the input JSON is well-formed before running, and no feedback loop for error recovery within the workflow itself. Error handling is listed separately without integration into the workflow steps.

2 / 3

Progressive Disclosure

The 18-row Actor table could be split into a separate reference file to keep the main skill lean. The skill references external scripts (`run_actor.js`) appropriately, but the inline content is heavy for a SKILL.md overview. No explicit links to supplementary documentation files.

2 / 3

Total

9

/

12

Passed

Description

32%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 identifies its domain (social media audience analysis) and lists relevant platforms, which provides some useful context. However, it lacks a 'Use when...' clause, uses somewhat abstract capability language rather than concrete actions, and could easily overlap with other social media or analytics skills. Adding explicit trigger guidance and more specific operations would significantly improve skill selection accuracy.

Suggestions

Add an explicit 'Use when...' clause with trigger terms like 'Use when the user asks about social media audience insights, follower demographics, engagement metrics, or audience analysis on Facebook, Instagram, YouTube, or TikTok.'

Replace abstract terms like 'understand' with concrete actions such as 'Analyzes audience demographics, segments followers by behavior patterns, measures engagement quality, and compares audience metrics across platforms.'

Include common user-facing synonyms and variations like 'social media analytics', 'follower insights', 'audience breakdown', 'social metrics' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (social media audience analysis) and some actions ('understand demographics, preferences, behavior patterns, engagement quality') but these are more like categories than concrete actions. It doesn't list specific operations like 'generate demographic reports', 'compare engagement rates', or 'segment audiences'.

2 / 3

Completeness

Describes what the skill does (understand audience data across platforms) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also somewhat vague, this scores a 1.

1 / 3

Trigger Term Quality

Includes relevant platform names (Facebook, Instagram, YouTube, TikTok) and some natural terms like 'audience demographics', 'engagement', and 'behavior patterns'. However, it's missing common user phrases like 'social media analytics', 'follower insights', 'audience analysis', or 'social metrics'.

2 / 3

Distinctiveness Conflict Risk

The mention of specific platforms (Facebook, Instagram, YouTube, TikTok) and focus on audience understanding provides some distinctiveness, but it could overlap with general social media analytics skills, content performance skills, or marketing analytics skills without clearer boundaries.

2 / 3

Total

7

/

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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