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apify-lead-generation

Scrape leads from multiple platforms using Apify Actors.

52

Quality

59%

Does it follow best practices?

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Adds up to 20 points to the overall score

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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/skills/apify-lead-generation/SKILL.md

The canonical home for this skill is apify-lead-generation in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

68%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 an efficient, actionable guide with a clear step sequence and a useful actor-selection table, but it lacks an explicit validation/verification checkpoint for this batch scraping operation, which caps workflow clarity.

Suggestions

Add a validation checkpoint between Step 4 and Step 5, e.g. verify the output file exists and is non-empty before summarizing, and show how to handle a zero-results run.

Consolidate the three near-duplicate Quick/CSV/JSON code blocks into a single invocation with documented optional --output and --format flags to tighten conciseness.

Briefly show how to construct the JSON_INPUT from the schema fetched in Step 2 so the run command is fully copy-paste ready.

DimensionReasoningScore

Conciseness

The body is lean, well-sectioned, and avoids explaining concepts Claude already knows; the three near-identical Quick/CSV/JSON code blocks could be consolidated into one with optional flags.

4 / 5

Actionability

It provides concrete executable commands (mcpc fetch, node script invocations) and a user-need-to-Actor-ID lookup table, but the JSON_INPUT placeholder is not shown constructed, leaving a minor gap.

4 / 5

Workflow Clarity

The 5-step sequence with a progress checklist is clear, but this batch scraping operation has no explicit validation checkpoint before summarizing, capping workflow clarity at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

Content is organized into clear sections (Prerequisites, Workflow, Error Handling) with a one-level-deep script reference; the inline 18-row actor table is an appropriate lookup rather than misplaced detail.

4 / 5

Total

15

/

20

Passed

Description

50%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 on-topic but minimal: it names the action and domain without listing the covered platforms or providing any trigger guidance. Adding a "Use when..." clause and platform keywords would lift all four dimensions.

Suggestions

Add a 'Use when...' clause naming concrete trigger scenarios, e.g. 'Use when the user wants to scrape leads or business contacts from Instagram, TikTok, Facebook, Google Maps, or Google Search.'

List the platforms supported (Instagram, TikTok, Facebook, Google Maps, etc.) as natural trigger terms so the description matches what users actually say.

Expand the action list beyond a single verb, e.g. 'Scrape, enrich, and export leads' to improve specificity.

DimensionReasoningScore

Specificity

"Scrape leads from multiple platforms using Apify Actors" names the domain and one concrete action (scrape), but offers only that single action rather than a comprehensive set.

3 / 5

Completeness

It states clearly what the skill does, but there is no "Use when..." clause or equivalent trigger guidance, capping completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

"Scrape leads" is a natural phrase, but the description omits the platform names (Instagram, TikTok, Facebook, etc.) and synonyms a user would actually say when needing this skill.

3 / 5

Distinctiveness Conflict Risk

The "Apify Actors" niche is somewhat specific, but "scrape leads from multiple platforms" is broad enough to overlap with other scraping or lead-generation skills.

3 / 5

Total

12

/

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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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