apify-lead-generation

Scrape leads from multiple platforms using Apify Actors.

Quality

59%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

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

Quality

Content

65%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 skill body is actionable and reasonably concise with a clear sequenced workflow and good error handling. Its main gaps are the missing validation checkpoint for a batch operation and the lack of progressive disclosure — the Actor table should live in a reference file.

Suggestions

Insert an explicit validation step in the workflow (e.g., verify the export file exists and the lead count is non-zero before summarizing), with a retry/fix loop on failure.

Move the 18-row Actor selection table into a references/ file (e.g., ACTORS.md) and link to it one level deep, keeping only a few representative examples inline.

Add at least one fully-worked example with a real Actor ID and input JSON so the Step 4 commands are copy-paste ready.

Dimension	Reasoning	Score
Conciseness	The body is mostly lean and assumes Claude's competence, with executable commands and a structured workflow rather than concept explanations. Minor padding ('No need to check it upfront' and the inline 'Best For' column) keeps it just below the fully lean anchor 5.	4 / 5
Actionability	Provides concrete, mostly executable bash/node commands for schema fetching and three output modes (quick/CSV/JSON) with real flags. It is not a 5 because placeholders like ACTOR_ID and JSON_INPUT prevent copy-paste readiness and no fully-worked example is shown.	4 / 5
Workflow Clarity	The 5-step checklist is clearly sequenced, but this is a batch scraping/export operation with no explicit validation checkpoint (e.g., verify the output file is non-empty or the lead count is sane) before reporting. Per the rubric, missing validation in batch operations caps workflow_clarity at 3.	3 / 5
Progressive Disclosure	Sections are well organized, but no reference bundle files exist and the large 18-row Actor selection table is inlined in SKILL.md rather than split into a one-level-deep reference. This matches anchor 3 (some structure, content that should be separate is inline) rather than 4's well-signaled split.	3 / 5
	Total	14 / 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 clear niche, but it omits any 'when to use' trigger guidance and lists only a single concrete action. Adding an explicit Use-when clause and a second concrete action would lift completeness and specificity.

Suggestions

Add a 'Use when ...' clause naming concrete trigger phrases (e.g., 'Use when the user wants to find business or creator leads, build prospect lists, or scrape contact data from social/maps/search platforms').

List at least one more concrete action beyond 'scrape leads' (e.g., 'export leads to CSV/JSON and summarize lead quality') to improve specificity.

Include common synonyms such as 'prospects' or 'outreach' so the description matches natural user phrasing.

Dimension	Reasoning	Score
Specificity	Names the domain (lead scraping from multiple platforms via Apify Actors) and one concrete action ('Scrape leads'), but offers only a single action rather than a comprehensive list. It sits at anchor 3 (domain + 1-2 concrete actions) and not 4, which requires several specific actions.	3 / 5
Completeness	It clearly states what the skill does but provides no 'Use when...' clause or equivalent trigger guidance for when Claude should invoke it. Per the judging guidelines, a missing explicit trigger caps completeness at 3 (clear 'what', missing 'when').	3 / 5
Trigger Term Quality	Includes natural terms a user might say ('scrape leads', 'platforms', 'Apify Actors') but misses common synonyms and variations like 'prospects', 'outreach', or 'contact data'. It fits anchor 3 (some relevant keywords, missing common variations) rather than 4's broader coverage.	3 / 5
Distinctiveness Conflict Risk	The Apify Actors niche and lead-scraping framing make it mostly distinct with only minor overlap risk against generic scraping skills. It is not a 5 because 'leads from multiple platforms' remains somewhat broad rather than a sharply bounded niche.	4 / 5
	Total	13 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: sickn33/agentic-awesome-skills
Path: skills/apify-lead-generation/SKILL.md
Commit: b1aebac

Reviewed: ~19 hours ago

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