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apify-lead-generation

Scrape leads from multiple platforms using Apify Actors.

56

Quality

64%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/apify-lead-generation/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

76%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 body is highly actionable with executable commands and a strong Actor selection table, and is reasonably concise and well-structured, but the batch export workflow lacks an explicit validation checkpoint in the main sequence.

Suggestions

Add an explicit validation/verification checkpoint in the main workflow (e.g. after Step 4, verify the output row count and spot-check fields before reporting) to lift workflow clarity above the batch cap.

Trim minor padding such as the "Copy this checklist and track progress" preamble and clarify the vague "Based on character of use case" guidance for number of results.

Signal the referenced runtime script more explicitly as a one-level reference (e.g. a short note that run_actor.js is provided by the plugin) to strengthen progressive disclosure.

DimensionReasoningScore

Conciseness

The body is mostly lean with exact bash commands and a tight actor table, but includes minor padding such as the "Copy this checklist and track progress" preamble and the vague "Based on character of use case" line, fitting the efficient-with-minor-trimming anchor.

4 / 5

Actionability

It provides fully executable, copy-paste-ready commands (mcpc fetch-actor-details and three run_actor.js variants for quick/CSV/JSON) plus a concrete Actor ID selection table, covering the common cases.

5 / 5

Workflow Clarity

A clear 5-step sequence exists with an error-handling section, but this batch lead-export operation lacks an explicit validate-before-proceeding checkpoint in the main flow, so the batch-operation cap holds it at 3.

3 / 5

Progressive Disclosure

Content is well-organized into clear sections with a one-level-deep reference to the runtime script; the long actor table is appropriately inlined as core decision content, with only minor organization gaps.

4 / 5

Total

16

/

20

Passed

Description

53%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 clear and appropriately specific about lead scraping via Apify, but lacks an explicit "Use when..." trigger clause and natural keyword variations, which keeps several dimensions at the midpoint.

Suggestions

Add an explicit "Use when..." clause naming concrete triggers, e.g. "Use when the user wants to find business, creator, or contact leads from Google Maps, Instagram, TikTok, Facebook, YouTube, or Google Search."

Expand trigger terms with natural synonyms and platform names users actually say (prospects, outreach, contact info, Instagram, TikTok, Google Maps) to raise trigger term quality.

List 2-3 more concrete actions (e.g. "discover prospects, extract contact data, export CSV/JSON") to move specificity toward comprehensive coverage.

DimensionReasoningScore

Specificity

"Scrape leads from multiple platforms using Apify Actors" names the domain and the scrape action with the tool, but does not enumerate the kinds of leads or operations, matching the 1-2 concrete actions anchor.

3 / 5

Completeness

It states a clear "what" but has no "Use when..." clause or equivalent trigger guidance, so per the missing-trigger guideline completeness is capped at 3.

3 / 5

Trigger Term Quality

Terms like "leads", "multiple platforms", and "Apify Actors" are relevant but miss common natural variations users say (prospects, outreach, contact info, platform names like Instagram/TikTok), fitting the some-relevant-keywords-but-missing-variants anchor.

3 / 5

Distinctiveness Conflict Risk

Lead generation via Apify Actors is a fairly distinct niche with only minor overlap risk against general scraping skills, fitting the mostly-distinct anchor rather than the niche-clear 5.

4 / 5

Total

13

/

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.

Validation15 / 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
sickn33/antigravity-awesome-skills
Reviewed

Table of Contents

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