klingai-async-workflows

tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill klingai-async-workflows

Build asynchronous video generation workflows with Kling AI. Use when integrating video generation into larger systems or pipelines. Trigger with phrases like 'klingai async', 'kling ai workflow', 'klingai pipeline', 'async video generation'.

53%

Overall

Validation — 81%

Implementation — 22%

Activation — 75%

SKILL.md

Review

Evals

Validation

81%

Warnings & errors only

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
metadata_version	'metadata' field is not a dictionary	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Implementation

22%

This skill is essentially a placeholder that describes what an async workflow skill should contain rather than providing actionable guidance. It lacks any executable code, concrete examples, or specific implementation details. The workflow steps are abstract directives that don't help Claude actually build async video generation pipelines.

Suggestions

Add executable code examples showing actual queue setup (e.g., Redis job enqueue), worker implementation, and state machine transitions

Replace abstract steps like 'Implement Queue' with specific code snippets showing how to enqueue a video generation job and poll for completion

Include a concrete state machine diagram or code showing job states (pending → processing → completed/failed) with validation checkpoints

Provide at least one complete, minimal working example inline rather than deferring all examples to external files

Dimension	Reasoning	Score
Conciseness	The content is relatively brief but includes some unnecessary filler like the generic overview and prerequisites that Claude would already understand. The actual workflow steps are vague rather than information-dense.	2 / 3
Actionability	The skill provides no executable code, no concrete commands, and only abstract descriptions like 'Set up job queue' and 'Build workers'. There's nothing copy-paste ready or specific enough to implement.	1 / 3
Workflow Clarity	The 5 steps listed are vague directives without concrete implementation details, validation checkpoints, or error recovery flows. For async workflows involving state machines and queues, this lacks the explicit validation and feedback loops required.	1 / 3
Progressive Disclosure	References to external files for errors and examples are present, but the main content is too thin to serve as a useful overview. The skill offloads all concrete guidance to other files without providing enough actionable content in the main file.	2 / 3
	Total	6 / 12 Passed

Activation

75%

This description has good structure with explicit 'Use when' and 'Trigger with' clauses, making it complete and distinctive. However, it lacks specific concrete actions (what exactly can be built/done) and the trigger terms lean toward technical jargon rather than natural user language.

Suggestions

Add specific concrete actions like 'submit generation jobs, poll for status, retrieve completed videos, handle callbacks'

Include more natural trigger phrases users might say, such as 'background video generation', 'batch video processing', 'queue Kling videos', or 'non-blocking video generation'

Dimension	Reasoning	Score
Specificity	Names the domain (asynchronous video generation with Kling AI) and mentions workflows/pipelines, but lacks specific concrete actions like 'submit generation jobs', 'poll for completion', 'retrieve video results', etc.	2 / 3
Completeness	Clearly answers both what ('Build asynchronous video generation workflows with Kling AI') and when ('Use when integrating video generation into larger systems or pipelines') with explicit trigger phrases provided.	3 / 3
Trigger Term Quality	Includes some relevant keywords ('klingai async', 'kling ai workflow', 'klingai pipeline', 'async video generation') but these feel technical/jargon-heavy rather than natural user phrases. Missing common variations like 'background video generation', 'batch video', or 'queue video'.	2 / 3
Distinctiveness Conflict Risk	Very specific niche combining Kling AI + async/workflow context. The 'klingai' prefix and async focus clearly distinguish it from general video generation or synchronous Kling AI skills.	3 / 3
	Total	10 / 12 Passed

Reviewed

16 days ago

Table of Contents

Validation Implementation Activation

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