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

76%

Does it follow best practices?

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Securityby

Medium

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

Quality

Content

85%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with a clear sequenced workflow, validation checkpoints, and clean progressive disclosure into real reference files; the main weakness is minor redundancy from the repeated description and the restated checklist.

Suggestions

Remove the verbatim description repetition at the top of the body, or replace it with a one-line orientation that adds new information.

Either fold the 'Actorization Checklist' into the step headers or reference the steps from it instead of duplicating the full list.

Note that js-ts-actorization.md links to ../../apify-actor-development/references/standby-mode.md outside this bundle; clarify or inline that guidance so the reference resolves within the skill.

Dimension	Reasoning	Score
Conciseness	Mostly tight and actionable, but the frontmatter description is repeated verbatim in the body and the 'Actorization Checklist' restates the eight steps that are then elaborated individually, adding redundancy that could be trimmed.	2 / 3
Actionability	Provides copy-paste-ready commands throughout (`apify init`, `apify run --input '...'`, `apify push`), a language install/wrap quick-reference table, and concrete schema JSON examples, all fully executable.	3 / 3
Workflow Clarity	An explicit 8-step sequence pairs with a pre-deployment checklist that validates against `@apify/json_schemas`, requires a successful `apify run` before `apify push`, and warns to use `apify run` over `npm start` — clear validation checkpoints for a deploy workflow.	3 / 3
Progressive Disclosure	SKILL.md is a concise overview with well-signaled, one-level-deep markdown links to real bundle files (js-ts-actorization.md, python-actorization.md, cli-actorization.md, schemas-and-output.md), keeping language-specific detail off the main page.	3 / 3
	Total	11 / 12 Passed

Description

67%Weight 40%Scale 1-3

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 specific and clearly occupies a distinct niche, but it lacks an explicit 'when to use' trigger clause and leans on technical jargon over natural user phrasings, capping completeness and trigger-term quality.

Suggestions

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

Include common user phrasings like 'actorize', 'Apify Actor', or 'package as an Apify Actor' alongside the technical terms.

Trim the definitional second sentence to keep the description concise while preserving the trigger guidance.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions and artifacts — 'converts existing software into reusable serverless applications', 'packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output' — matching the multi-action anchor.	3 / 3
Completeness	Clearly answers 'what' the skill does but provides no 'Use when...' clause or equivalent trigger guidance, so per the rubric guideline completeness is capped at 2.	2 / 3
Trigger Term Quality	Contains relevant niche terms ('Actorization', 'Apify platform', 'Actors', 'Docker images') a user in this ecosystem would say, but leans technical and omits common phrasings like 'actorize a project' or 'convert to an Apify Actor'.	2 / 3
Distinctiveness Conflict Risk	The Apify Actorization niche is highly specific with distinct terminology, making it unlikely to trigger for unrelated skills.	3 / 3
	Total	10 / 12 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/antigravity-awesome-skills
Path: skills/apify-actorization/SKILL.md
Commit: 07da495

Reviewed: 7 days ago

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