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apify

Apify integration. Manage Actors, Datasets, KeyValueStores, RequestQueues, Tasks. Use when the user wants to interact with Apify data.

Quality

76%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/apify/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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 highly actionable and the connection workflow has explicit state-based checkpoints, but token efficiency suffers from an empty resource bullet-tree and persona padding, and all detail lives in one file with no progressive disclosure. Broken cross-references ("Step 2") and absent run-monitoring guidance are the main clarity gaps.

Suggestions

Cut the Apify Overview bullet tree and the user-persona sentence; replace with one line naming the resource types or move the taxonomy into a reference file.

Fix the dangling "skip to Step 2" references (there is no Step 2 heading) and add a short workflow for monitoring an async run to completion (e.g., poll get-run until status is terminal).

Move the Popular actions catalog and proxy flag table into a references/ file, keeping a handful of high-frequency actions inline, so SKILL.md stays an overview with one-level-deep references.

DimensionReasoningScore

Conciseness

The command sections are tight, but there is real padding: the "used by data scientists, marketers, and researchers" persona sentence, the 18-line "Apify Overview" bullet tree whose sub-entries are just "Run"/"Record"/"Request" plus the vacuous "Use action names and parameters as needed.", and the "so you can focus on the integration logic rather than auth plumbing" aside. Not a 4 because these unnecessary explanations go beyond minor instances.

3 / 5

Actionability

Nearly every section gives copy-paste-ready commands (npm install, membrane login with headless variant, connection ensure, action list/run with --input, request with a flags table), and the Popular actions table catalogs 19 concrete actions. Not a 5 because the run examples stay at placeholder level (no worked end-to-end example with a real actionId and input) and the table gives keys where the run command needs an actionId.

4 / 5

Workflow Clarity

The setup sequence is clear with genuine checkpoints: poll with --wait, state-by-state handling of READY/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR, and re-poll after user action. Not a 5 because "skip to Step 2" references a step that is never defined (and "1b" has no "1a"), and there is no guidance on monitoring an async run to completion after Run Actor/Run Task returns immediately.

4 / 5

Progressive Disclosure

The single SKILL.md has clear section headers, but there is no bundle at all — the 19-row Popular actions catalog and the proxy flag table are exactly the bulk material a reference file would hold, and everything is inlined. Anchor 3 ("content that should be separate is inline") fits better than 4 given ~165 lines with zero one-level-deep references.

3 / 5

Total

14

/

20

Passed

Description

78%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, specific, and third-person, with a clear what and an explicit Use-when clause that anchors it to the Apify niche. Its main weakness is the generic "Manage" verb and a when-clause that misses high-frequency natural triggers like scraping and crawling.

Suggestions

Replace the generic "Manage" with distinct concrete actions, e.g., "Run Actors and Tasks, abort runs, fetch dataset and key-value store items, manage request queues."

Sharpen the when-clause with concrete triggers: "Use when the user mentions Apify, actor runs, scraping datasets, or getting crawl results."

Add natural synonyms such as web scraping or crawling so the skill surfaces for scraping-related requests that don't name Apify.

DimensionReasoningScore

Specificity

"Manage Actors, Datasets, KeyValueStores, RequestQueues, Tasks" enumerates five concrete Apify resource types, giving several specific capabilities with only minor coverage gaps. It falls short of a 5 because the single generic verb "Manage" replaces distinct concrete actions (e.g., run actors, fetch dataset items, abort runs).

4 / 5

Completeness

The "what" is explicit ("Apify integration. Manage Actors, Datasets, KeyValueStores, RequestQueues, Tasks.") and the "when" is present as an explicit "Use when" clause. It is not a 5 because "Use when the user wants to interact with Apify data" is generic and lacks concrete trigger phrases (e.g., mentions of Apify, actor runs, or scraping datasets).

4 / 5

Trigger Term Quality

Terms like "Apify", "Actors", "Datasets", "Tasks" match what users of the platform naturally say. A few natural terms are missing — notably "scrape/scraping", "crawl", and "web automation", which are among the most common reasons users reach for Apify.

4 / 5

Distinctiveness Conflict Risk

"Apify integration" names a clear niche with platform-specific triggers (Apify, Actors, Datasets, KeyValueStores, RequestQueues, Tasks) that no other skill category would claim, so conflict risk is minimal.

5 / 5

Total

17

/

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

membranedev/application-skills

Path

skills/apify/SKILL.md

Reviewed

Table of Contents

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