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apify-lead-generation

Scrape leads from multiple platforms using Apify Actors.

54

Quality

61%

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-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 content is well-structured, concise, and actionable with a clear sequenced workflow, but the batch scraping operation lacks an explicit validation checkpoint, capping workflow clarity. The referenced run_actor.js script could not be verified in the bundle.

Suggestions

Add a validation checkpoint after scraping (e.g. verify the output file is non-empty, row count matches expectations, and spot-check required fields) before reporting success in Step 5.

Replace the 'JSON_INPUT' placeholder with a concrete example input for at least one Actor so the command is fully copy-paste ready.

Confirm the run_actor.js script exists at the referenced path (reference/scripts/run_actor.js) or correct the path so the bundle matches the documented commands.

DimensionReasoningScore

Conciseness

The body is efficient and assumes competence, with a dense Actor-selection table and runnable commands rather than explanations of what Apify is; only minor redundancy (the H1 re-states the description).

4 / 5

Actionability

Provides concrete, mostly copy-paste bash commands with the run_actor.js script invocation, though 'JSON_INPUT' remains an unfilled placeholder and the referenced script path cannot be verified against an absent bundle scripts directory.

4 / 5

Workflow Clarity

A clear 5-step sequenced checklist is present, but this batch lead-scraping workflow has no validation/verification checkpoint, so per the rubric's batch-operation cap workflow clarity cannot exceed 3.

3 / 5

Progressive Disclosure

A single well-organized overview file with clear section headers and no nested references; the only gap is the asserted run_actor.js reference whose bundle location could not be confirmed.

4 / 5

Total

15

/

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 specific about the domain and tooling but lacks a 'Use when...' trigger clause and richer natural-language keywords, leaving it mid-range across most dimensions. It is reasonably distinct from other skills.

Suggestions

Add a 'Use when...' clause naming concrete triggers, e.g. 'Use when the user wants to build a contact list, find B2B leads, or extract emails/phones from platforms like Instagram, TikTok, Facebook, or Google Maps.'

Expand the action verbs beyond 'Scrape' to reflect the breadth implied by the Actor table (e.g. 'extract contact info, enrich profiles, and export leads').

Include natural synonyms users would say ('lead list', 'email finder', 'contact scraper') to improve trigger-term coverage.

DimensionReasoningScore

Specificity

Names the domain (lead scraping) and a concrete tool ('Apify Actors') but only lists the single action 'Scrape leads from multiple platforms', which matches the 'domain and 1-2 concrete actions, not comprehensive' anchor.

3 / 5

Completeness

Provides a clear 'what' (scrape leads via Apify Actors) but has no 'Use when...' trigger clause, and the rubric caps completeness at 3 when such guidance is missing.

3 / 5

Trigger Term Quality

Includes relevant terms ('leads', 'multiple platforms', 'Apify Actors') but omits natural user phrases and synonyms like 'contact list', 'email finder', or 'B2B leads', matching the 'some relevant keywords but missing variations' anchor.

3 / 5

Distinctiveness Conflict Risk

The Apify-based lead-scraping niche is mostly distinct with only minor overlap risk against general scraping skills, fitting just above the 'somewhat specific' anchor.

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

Table of Contents

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