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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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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 ./skills/apify-lead-generation/SKILL.md
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 action-dense and well-organized, giving Claude concrete commands and a clear actor-selection table. Its main weaknesses are the absence of any output-validation checkpoint in a batch workflow and no example input payload to make the run command fully copy-paste ready.

Suggestions

Add an explicit validation step before Step 5, e.g. verify the output file exists and is non-empty (or check the returned item count) before summarizing results.

Include one concrete example JSON_INPUT for a representative actor (e.g. a Google Places search query with location and max results) so the run command is immediately executable.

Move per-actor usage notes or the full actor catalog into a references/ file, keeping SKILL.md as a lean overview with well-signaled one-level-deep references.

DimensionReasoningScore

Conciseness

The body is dense and efficient — a compact actor-selection table, terse commands, and a lean error table — with only minor trimmable filler such as "(No need to check it upfront)", "Based on character of use case", and generic boilerplate limitation lines.

4 / 5

Actionability

Provides copy-paste-ready bash commands for all three output formats plus a concrete mcpc schema-fetch command and an error-message-to-fix table, but no example JSON_INPUT for any actor, leaving a minor gap for the most common case.

4 / 5

Workflow Clarity

Five clearly sequenced steps with a progress checklist and error recovery are present, but this is a batch operation (paid actor runs, bulk lead exports) with no explicit validation or verification step before reporting results, which the rubric caps at 3.

3 / 5

Progressive Disclosure

A well-sectioned single file with no nested references and the actor table appropriately inline as core decision content; minor gaps in that the 17-row actor catalog could live in a reference file and the referenced script is outside this bundle.

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 concise and names a concrete action with a distinctive tool, but it lacks any explicit 'when to use' trigger guidance and misses natural keywords for the covered platforms. Adding a 'Use when...' clause with platform and use-case triggers would raise completeness and trigger-term quality substantially.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user needs business or contact leads, prospect lists, or outreach data from platforms like Google Maps, Instagram, TikTok, or Facebook."

Include the downstream capabilities in the 'what': exported CSV/JSON lead lists plus a summary of lead quality or segmentation.

Add natural synonyms such as "lead generation", "prospects", and "contact info" so the description matches how users actually phrase these requests.

DimensionReasoningScore

Specificity

"Scrape leads from multiple platforms using Apify Actors" names the domain and one concrete action but omits the export and summarization capabilities the skill actually performs, matching '1-2 concrete actions, but not comprehensive'.

3 / 5

Completeness

The 'what' is clear (scrape leads via Apify Actors) but there is no 'Use when...' clause or equivalent trigger guidance, which the rubric caps at 3.

3 / 5

Trigger Term Quality

"leads", "scrape", and "Apify" are natural terms, but common variations users would say — "lead generation", "contact info", "emails", "prospects", "outreach", and platform names like Google Maps/Instagram/TikTok — are missing.

3 / 5

Distinctiveness Conflict Risk

"Apify Actors" carves a distinct niche with minimal conflict risk, but "multiple platforms" is broad enough to overlap with generic scraping skills, so it falls just short of a clear-niche 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.

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
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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