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

64%

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

Quality

Content

71%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.

A well-structured, actionable guide with excellent progressive disclosure into a real reference bundle and a clearly sequenced workflow with pre-deployment validation. Its main weakness is redundancy — the same step sequence is repeated three times and the intro duplicates the description — which costs tokens without adding information.

Suggestions

Collapse the 'Quick Start' and 'Actorization Checklist' sections into a single sequence; the current layout repeats the same 8 steps three times.

Remove the verbatim re-statement of the frontmatter description in the opening paragraph and replace it with a one-line purpose statement.

Add a short validate→fix→retry note for schema validation failures (e.g., what to do when `@apify/json_schemas` rejects actor.json) to close the feedback-loop gap.

Dimension	Reasoning	Score
Conciseness	The body is mostly lean command-first prose, but the same 8-step flow is stated three times ("Quick Start", the "Actorization Checklist", and the numbered Step sections), and the opening paragraph repeats the frontmatter description verbatim. This matches 'mostly efficient but could be tightened' rather than the minor-trim level of 4.	3 / 5
Actionability	Concrete, executable commands appear throughout (`apify init`, `apify run --input '{"startUrl": "https://example.com", "maxItems": 10}'`, `apify push`, `apify info`), plus a language quick-reference table and explicit validation via `@apify/json_schemas`. It falls short of 5 only because the core wrapping code lives in reference files rather than the body itself.	4 / 5
Workflow Clarity	A clearly sequenced 8-step process with two checklists, a local-test gate ('`apify run` executes successfully with test input') before deploy, and explicit schema validation ('validates against `@apify/json_schemas`'). Not 5 because there is no validate→fix→retry feedback loop for failed builds or schema validation errors.	4 / 5
Progressive Disclosure	The SKILL.md is a genuine overview: language-specific detail is split into four real, verified one-level-deep reference files (js-ts-actorization.md, python-actorization.md, cli-actorization.md, schemas-and-output.md), each linked with a clear statement of what it contains, with no nested references. This matches the anchor for a clear overview with well-signaled references.	5 / 5
	Total	16 / 20 Passed

Description

57%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.

A distinctive, concrete description that clearly says what the skill does, with strong domain-specific trigger terms and essentially no conflict risk. Its main gaps are the complete absence of when-to-use guidance and missing natural trigger variations users would actually say.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when converting a script, CLI tool, or Crawlee project into an Apify Actor, or when the user mentions Apify, Actors, or deploying to the Apify platform.'

Include natural trigger synonyms users would say — 'wrap a script', 'migrate to Apify', 'deploy to Apify', 'Crawlee', '.actor' — to strengthen keyword coverage.

Lead with 2-3 concrete actions (e.g. 'Wraps existing code with the Apify SDK, defines input/output schemas, and deploys as a Docker image') instead of the more definitional current phrasing.

Dimension	Reasoning	Score
Specificity	It names the domain and one concrete action — 'converts existing software into reusable serverless applications' — plus concrete mechanics ('programs packaged as Docker images that accept well-defined JSON input... produce structured JSON output'). It does not list several specific actions, so it matches '1-2 concrete actions, not comprehensive' rather than the 'several specific actions' of 4.	3 / 5
Completeness	The 'what' is clearly and concretely answered (convert software into Apify Actors, packaged as Docker images with JSON input/output), but there is no 'when to use it' clause at all. Per the judging guidelines, a missing 'Use when...' clause caps completeness at 3.	3 / 5
Trigger Term Quality	'Apify platform' and the Actor/Docker/JSON vocabulary are relevant keywords a user in this niche would say, but common natural variations are missing: no 'wrap a script', 'migrate to Apify', 'deploy to Apify', 'Crawlee', or '.actor' terms. This fits 'some relevant keywords but missing common variations or synonyms' rather than the good-coverage anchor of 4.	3 / 5
Distinctiveness Conflict Risk	'Actorization' and 'the Apify platform' carve out a clear niche with distinct triggers; virtually no other skill would compete for this description. It matches 'clear niche with distinct triggers; minimal conflict risk'.	5 / 5
	Total	14 / 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: c26b706

Reviewed: 2 hours ago

Table of Contents

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