klingai-model-catalog

Explore Kling AI models, versions, and capabilities for video and image generation. Use when selecting models or comparing features. Trigger with phrases like 'kling ai models', 'klingai capabilities', 'kling video models', 'klingai features'.

Quality

—

Does it follow best practices?

Impact

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No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

92%

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

The body is an efficient, actionable reference catalog with a clear selection flow, scoring well on conciseness, actionability, and workflow clarity. Its one weakness is progressive disclosure: it duplicates content already present in references/ bundle files without ever pointing to them.

Suggestions

Replace the inline Video/Image model tables with a concise summary and link to references/available-models.md for full per-model capabilities, keeping the body as an overview.

Move the Model Selection Decision Tree into references/model-selection-logic.md (or link to it) and reference it from the body so the selection logic lives in one place rather than being duplicated.

Add a "References" section that explicitly signals each bundle file (e.g., errors.md, examples.md, generation-types.md) so Claude can navigate to detail one level deep instead of everything living inline.

Dimension	Reasoning	Score
Conciseness	The body is a lean, table-driven catalog with no concept-explanation fluff (no "what is video generation" padding); every section delivers reference data that earns its tokens.	3 / 3
Actionability	It gives concrete model IDs, endpoint paths, credit costs, a copy-paste-ready `requests.post` snippet, and a decision tree that maps requirements directly to a specific model and mode.	3 / 3
Workflow Clarity	The Model Selection Decision Tree provides an unambiguous if/then selection flow; as a lookup/reference skill with no destructive or batch operations, no validation checkpoint is warranted, so the clear flow suffices.	3 / 3
Progressive Disclosure	Bundle files exist (references/available-models.md, model-selection-logic.md) that overlap the inline model tables and selection logic, yet the body never signals or links to any of them, leaving ~110 lines of reference content inline that could live in those files — matching the "content that should be separate is inline; references not clearly signaled" anchor.	2 / 3
	Total	11 / 12 Passed

Description

90%

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 strong description: it states a clear niche, gives explicit "Use when" trigger guidance, and lists natural trigger phrases a user would say. The only soft spot is specificity, where a single high-level verb ("Explore") substitutes for a list of concrete actions.

Dimension	Reasoning	Score
Specificity	The description names the domain and a few actions ("Explore Kling AI models, versions, and capabilities", "selecting models or comparing features") but relies on the single verb "Explore" rather than listing multiple concrete actions, matching the "names domain and some actions, but not comprehensive" anchor.	2 / 3
Completeness	It explicitly answers both what ("Explore Kling AI models… for video and image generation") and when ("Use when selecting models or comparing features") plus explicit trigger phrases, matching the top anchor.	3 / 3
Trigger Term Quality	It supplies natural phrases a user would actually say — "'kling ai models'", "'klingai capabilities'", "'kling video models'", "'klingai features'" — giving good coverage of the niche's natural terms.	3 / 3
Distinctiveness Conflict Risk	Kling AI is a specific niche and the trigger phrases are distinctive to it, making conflict with unrelated skills unlikely.	3 / 3
	Total	11 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: 3022dd3

Reviewed: 1 day ago

Table of Contents

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