apify-ecommerce

Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

Quality

65%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/apify-ecommerce/SKILL.md

Quality

Content

65%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 lean and highly actionable with concrete commands and JSON examples per workflow, but it lacks an explicit validation checkpoint for its batch extraction operations and references a script file that is absent from the bundle. Both gaps cap workflow_clarity and progressive_disclosure at 3.

Suggestions

Add an explicit validation/verification step after running the actor (e.g. check the result count against maxProductResults/maxReviewResults, surface partial-failure warnings, and retry or adjust input before reporting).

Ship the referenced `run_actor.js` under a `references/scripts/` (or `scripts/`) bundle directory, or correct the `$SKILL_PATH/reference/scripts/` path so the referenced file actually exists.

Replace unresolved placeholders (`JSON_INPUT`, `YYYY-MM-DD_filename`) with concrete substitution guidance or a worked example so commands are fully copy-paste ready.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient — tables, tight code blocks, and field lists with no padding explaining concepts Claude already knows; the only redundancy is the description repeated verbatim as the opening line, which could be trimmed.	4 / 5
Actionability	Provides concrete, copy-paste-ready `node --env-file` commands and worked JSON input examples for each workflow, plus an output-fields list and error-handling table; minor gaps remain in placeholders like `JSON_INPUT` and `YYYY-MM-DD_filename` that the agent must still resolve.	4 / 5
Workflow Clarity	A progress checklist and numbered running/summarize steps give a clear sequence, and an error-handling table covers failures, but for a batch extraction skill there is no explicit validate-checkpoint (e.g. confirm item count or inspect partial results) before reporting, so the rubric's batch-operation cap of 3 applies.	3 / 5
Progressive Disclosure	The body is well organized with clear sections and signals a one-level reference to `$SKILL_PATH/reference/scripts/run_actor.js`, but no `references/`, `scripts/`, or `assets/` bundle directory exists, so the referenced script is not a real file and navigation breaks; the guideline to score against the actual bundle structure lowers this to 3.	3 / 5
	Total	14 / 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.

The description is specific and actionable, naming the tool and four concrete data types with natural trigger terms, but it omits an explicit 'when to use' clause, which the rubric caps at completeness 3. Distinctiveness is strong thanks to the named Apify tool.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user needs product, pricing, review, stock, or seller data from e-commerce sites or mentions price monitoring, MAP enforcement, or competitor analysis.'

Broaden trigger synonyms to include terms users naturally say like 'scrape', 'pricing', 'stock', and major marketplace names (Amazon, Walmart).

Vary the action verbs beyond a single 'Extract' to better reflect distinct capabilities (e.g. extract, compare, monitor, analyze).

Dimension	Reasoning	Score
Specificity	Lists several concrete extraction targets ('product data, prices, reviews, and seller information') tied to a named tool, but a single verb ('Extract') repeats rather than covering distinct actions, so it stops short of comprehensive coverage.	4 / 5
Completeness	The 'what' is clear ('Extract product data, prices, reviews, and seller information from any e-commerce platform'), but there is no explicit 'Use when...' / trigger clause, so per the rubric guideline a missing trigger clause caps completeness at 3.	3 / 5
Trigger Term Quality	Includes natural terms users would say ('product data', 'prices', 'reviews', 'seller information', 'e-commerce') plus 'Scraping' via the tool name, but misses common synonyms such as 'scrape', 'pricing', or marketplace names that users often mention.	4 / 5
Distinctiveness Conflict Risk	Naming a specific tool ('Apify's E-commerce Scraping Tool') and a concrete domain ('e-commerce platform') carves a clear niche with low conflict risk, though the broad phrasing 'any e-commerce platform' leaves minor overlap with general scraping skills.	4 / 5
	Total	15 / 20 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-ecommerce/SKILL.md
Commit: 1f67c44

Reviewed: about 16 hours ago

Table of Contents

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