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apify-ecommerce

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

60

Quality

71%

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-ecommerce/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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 highly actionable with concrete commands and examples, but the batch extraction workflow lacks an embedded validation checkpoint and all detail is inlined into a single file rather than progressively disclosed.

Suggestions

Insert an explicit validation checkpoint in the run sequence, e.g. 'Verify result count > 0 and spot-check fields before summarizing; if empty, consult the error table and retry.'

Move the long Supported Marketplaces list and per-workflow input schemas into a reference file (e.g. references/marketplaces.md) and link from SKILL.md.

Remove the verbatim repeat of the frontmatter description under the H1 to trim tokens.

DimensionReasoningScore

Conciseness

The body is efficient actionable reference (JSON inputs, field tables, commands, error table) with no concept-explanation fluff; minor trim opportunities exist in the repeated intro line and per-workflow 'Best for:' audience labels.

4 / 5

Actionability

Copy-paste ready 'node --env-file=...' commands, the concrete Actor ID 'apify/e-commerce-scraping-tool', per-workflow JSON input examples, and --format/--output flags cover the common cases fully.

5 / 5

Workflow Clarity

A 5-step progress checklist and 3-step run sequence exist with an error-handling table, but this batch extraction workflow lacks an explicit validation checkpoint (e.g. verify result count before summarizing), capping it at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

Section structure is good, but everything is inlined into one monolithic SKILL.md with no reference docs split out; the only external reference (reference/scripts/run_actor.js) is not present as a bundle file, and long marketplace lists and per-workflow schemas could live in separate files.

3 / 5

Total

15

/

20

Passed

Description

71%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 names concrete capabilities with a clear niche, but it omits any 'Use when...' trigger guidance and leans on broad 'any e-commerce platform' phrasing that invites some overlap risk.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user wants to scrape product data, prices, reviews, or sellers from e-commerce sites like Amazon, Walmart, or IKEA.'

Add natural synonyms users actually say ('scrape', 'pricing', 'competitor prices', 'sentiment') to broaden trigger coverage.

Tighten 'from any e-commerce platform' toward the specific marketplaces supported to reduce overlap with generic scraping skills.

DimensionReasoningScore

Specificity

Quotes 'Extract product data, prices, reviews, and seller information' — four concrete extraction targets naming exactly what the tool outputs, with comprehensive coverage rather than minor gaps.

5 / 5

Completeness

A clear 'what' is present (extract product data, prices, reviews, seller info), but there is no 'Use when...' clause or equivalent explicit trigger guidance, capping completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Natural domain terms ('product data', 'prices', 'reviews', 'seller information', 'e-commerce') give good coverage, but common synonyms like 'scrape', 'pricing', or 'competitor prices' are absent.

4 / 5

Distinctiveness Conflict Risk

The Apify e-commerce scraping niche is mostly distinct, but 'from any e-commerce platform' is broad enough to risk minor overlap with other scraping or data-extraction skills.

4 / 5

Total

16

/

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
Reviewed

Table of Contents

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