apify-ultimate-scraper

AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.

Quality

56%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/apify-ultimate-scraper/SKILL.md

Quality

Content

77%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable and clearly sequenced with strong validation gates, but it front-loads a bulky actor catalog inline and references a script file that is not present in the bundle, limiting its progressive-disclosure quality.

Suggestions

Move the per-platform actor catalog tables into a reference file (e.g. references/actors.md) and keep SKILL.md as an overview that links to it one level deep.

Ensure the referenced ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js actually exists under references/scripts/, or correct the path so the bundle structure matches the body.

Tighten the catalog by collapsing 'Best For' columns into a compact reference, reducing token weight while preserving discoverability.

Dimension	Reasoning	Score
Conciseness	Prose sections are tight and avoid explaining concepts Claude already knows, but the body inlines a large 55-actor catalog plus several reference tables that could be moved to a separate file, so it could be tightened.	2 / 3
Actionability	It provides fully executable, copy-paste-ready commands (mcpc tools-call invocations and `node --env-file=.env .../run_actor.js` with concrete flags and placeholders) plus real actor IDs and a search fallback.	3 / 3
Workflow Clarity	A clear 5-step sequence with a copyable progress checklist, prerequisites, an explicit cost/approval checkpoint before paid runs, and an error-handling section provide explicit validation steps and feedback loops.	3 / 3
Progressive Disclosure	Sections are well organized, but content that should be separate (the full actor catalog) is inlined, and the one referenced script path (${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js) has no corresponding references/scripts/ directory in the bundle.	2 / 3
	Total	10 / 12 Passed

Description

35%Weight 40%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 conveys a recognizable Apify scraping niche but is weakened by technical jargon and the complete absence of natural trigger terms or an explicit 'Use when' clause. It reads as a capability statement rather than trigger guidance.

Suggestions

Add an explicit 'Use when...' clause with concrete triggers, e.g. 'Use when the user needs to scrape social profiles, posts, comments, reviews, or business listings across Instagram, Facebook, TikTok, YouTube, Google Maps, or X.'

Replace Apify jargon ('Actors', 'AI-driven data extraction') with natural user keywords such as 'scrape', 'extract posts', 'pull reviews', and platform names.

List a few concrete actions (profile scraping, comment extraction, review aggregation) instead of the generic 'data extraction' to lift specificity.

Dimension	Reasoning	Score
Specificity	It names a clear domain ('data extraction from 55+ Actors across all major platforms') and a concrete mechanism ('automatically selects the best Actor'), but does not enumerate the specific actions (profiles, posts, reviews, leads), so it is not comprehensive.	2 / 3
Completeness	It states what the skill does but offers no explicit 'Use when...' trigger, so the 'when' is only weakly implied, which caps completeness at 2.	2 / 3
Trigger Term Quality	It relies on Apify jargon ('AI-driven data extraction', 'Actors') and contains none of the natural terms a user would say ('scrape', 'Instagram', 'TikTok', 'reviews', 'leads').	1 / 3
Distinctiveness Conflict Risk	The multi-platform Apify framing gives it a recognizable niche, but 'data extraction across all major platforms' is broad and lacks distinct triggers, so it could overlap with other scraping skills.	2 / 3
	Total	7 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: sickn33/antigravity-awesome-skills
Path: skills/apify-ultimate-scraper/SKILL.md
Commit: 07da495

Reviewed: 8 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.