apify-actorization

Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

Quality

70%

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Securityby

Passed

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tessl review fix ./skills/apify-actorization/SKILL.md

Quality

Content

78%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 well-structured, actionable, and cleanly splits detail into one-level references with strong progressive disclosure. Its main weakness is that the deploy/batch validation lives in a checklist rather than an embedded feedback loop.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with checklists, tables, and references; only minor instances of over-explanation such as the token-handling narration could be trimmed.	4 / 5
Actionability	Provides concrete executable commands (apify init, apify run --input, apify push) and a quick-reference table; language-specific code is deferred to references leaving only minor gaps.	4 / 5
Workflow Clarity	Clear 8-step sequence with a pre-deployment validation checklist and a guardrail to use `apify run`; minor gaps because the main flow embeds no explicit validate-fix-retry feedback loop around deploy.	4 / 5
Progressive Disclosure	Clear overview in SKILL.md points to one-level-deep references (js-ts, python, cli, schemas-and-output), all real files in references/ and well-signaled with markdown links.	5 / 5
	Total	17 / 20 Passed

Description

62%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 clearly and specifically defines the actorization capability and occupies a distinct niche, but omits an explicit 'Use when' trigger clause and relies on technical jargon over natural user phrases.

Suggestions

Add an explicit 'Use when...' clause naming natural triggers, e.g. 'Use when converting a CLI tool, script, or Crawlee project into an Apify actor.'

Incorporate natural user phrasings and synonyms such as 'Apify actor', 'deploy to Apify', and 'wrap as an actor' to improve trigger-term coverage.

Tighten the 'what' from a definition of actors toward concrete actions the skill performs (convert, wrap, configure, deploy).

Dimension	Reasoning	Score
Specificity	Lists several specific concrete characteristics ('converts existing software into reusable serverless applications', 'packaged as Docker images', 'accept well-defined JSON input', 'produce structured JSON output') with only minor gaps.	4 / 5
Completeness	Clearly states what the skill does but lacks any explicit 'Use when...' trigger guidance, which per the rubric caps completeness at 3.	3 / 5
Trigger Term Quality	Includes relevant platform terms ('Actorization', 'Apify platform', 'serverless applications', 'Docker images') but misses common natural variations like 'actor', 'deploy to Apify', or 'wrap as actor'.	3 / 5
Distinctiveness Conflict Risk	'Actorization' and 'Apify platform' define a clear niche with distinct triggers and minimal conflict risk with other skills.	5 / 5
	Total	15 / 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-actorization/SKILL.md
Commit: b1aebac

Reviewed: ~18 hours ago

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