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apify-content-analytics

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

Quality

75%

Does it follow best practices?

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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-content-analytics/SKILL.md

The canonical home for this skill is apify-content-analytics in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 an efficient, actionable, well-sequenced workflow: select an Actor from a table, fetch its live schema via mcpc, ask preferences, run a script, summarize. Main gaps are the missing example of an actor input JSON, three redundant command variants, and no explicit output-verification checkpoint for batch actor runs.

Suggestions

Add one concrete example of --input JSON for a representative Actor (e.g., apify/instagram-post-scraper with a post URL) so the placeholder is immediately usable.

Collapse the three quick/CSV/JSON bash blocks into a single command showing the optional --output/--format flags.

Add a verification checkpoint after Step 4 (e.g., confirm the output file exists and is non-empty before reporting, and re-check failed runs via the Apify console link) to close the batch-operation validation gap.

DimensionReasoningScore

Conciseness

The body is lean: an actor-selection table, concrete commands, and step headings with no explanations of concepts Claude already knows. It is not 5 because the three near-duplicate bash blocks for quick/CSV/JSON differ only in flags and could be one command, and the parenthetical "(No need to check it upfront)" is filler.

4 / 5

Actionability

Commands are executable and specific (the mcpc tools-call invocation with auth header, and run_actor.js with --actor/--input/--output/--format flags). It is not 5 because JSON_INPUT is a never-exemplified placeholder — no sample actor input JSON is given, and the referenced run_actor.js script is not part of the bundle to verify.

4 / 5

Workflow Clarity

A clear 5-step sequence with a copyable progress checklist, a pre-run schema fetch in Step 2, and an Error Handling section with recovery actions (e.g., Timeout → reduce input or increase --timeout). It is not 5 because there is no explicit output verification step after a batch actor run — Step 5 only asks to report results, not validate them.

4 / 5

Progressive Disclosure

A single well-organized file with clear per-step sections, no nested or buried references, and an external script correctly kept out of the SKILL.md. It is not 5 because at ~110 lines the 17-row actor table is borderline content that could live in a reference file, and no reference files exist to demonstrate one-level-deep disclosure.

4 / 5

Total

16

/

20

Passed

Description

66%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.

A concise, platform-specific description with concrete action verbs and good natural trigger terms. Its main weakness is the complete absence of a 'when to use' clause, which caps completeness and slightly weakens trigger coverage.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks about social media performance, engagement, or campaign ROI on Instagram, Facebook, YouTube, or TikTok.'

Broaden trigger terms with common synonyms users say, such as 'social media analytics', 'post performance', 'followers', or 'likes/comments'.

Optionally name the concrete operation (scraping via Apify Actors and exporting CSV/JSON) to sharpen the 'what' beyond broad analytics verbs.

DimensionReasoningScore

Specificity

The description lists three concrete actions ("Track engagement metrics, measure campaign ROI, and analyze content performance") and names four platforms, matching the 'several specific actions with minor gaps' anchor. It falls short of 5 because the actions are broad verbs with no concrete operations (scraping, exporting, reporting) that would make coverage comprehensive.

4 / 5

Completeness

The 'what' is clearly stated (track metrics, measure ROI, analyze performance), but there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines. It is not lower because the 'what' half is explicit and specific.

3 / 5

Trigger Term Quality

"engagement metrics", "campaign ROI", and the platform names (Instagram, Facebook, YouTube, TikTok) are phrases users naturally say when needing this skill. It is not 5 because common variations such as "social media analytics", "followers", "likes", or "post performance" are absent.

4 / 5

Distinctiveness Conflict Risk

The four-platform scope plus engagement/ROI framing gives it a distinct niche with unlikely mis-triggering. It is not 5 because the broad "content performance" framing could overlap with per-platform scraper or general analytics skills.

4 / 5

Total

15

/

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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/apify-content-analytics/SKILL.md

Reviewed

Table of Contents

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