klingai-image-to-video

Animate static images into video using Kling AI. Use when converting images to video, adding motion to stills, or building I2V pipelines. Trigger with phrases like 'klingai image to video', 'kling ai animate image', 'klingai img2vid', 'animate picture klingai'.

Quality

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Does it follow best practices?

Impact

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No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

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 content is lean, highly actionable, and presents a clear workflow with feedback loops. Its main weakness is progressive disclosure: advanced material is inlined and the bundled reference files are not surfaced from SKILL.md.

Suggestions

Link to the existing reference files from the body (e.g. 'See motion-control-options.md for camera/motion brush details', 'See batch-image-processing.md for multi-image workflows') so the bundle is discoverable.

Move the advanced variation examples (image_tail, dynamic_masks, static_mask) and the full parameter/error tables into references/ to keep SKILL.md a concise overview.

Add a brief validation note (e.g. HTTP status check, max poll attempts) to the polling loop to make the workflow's failure path more explicit.

Dimension	Reasoning	Score
Conciseness	The body is lean tables and executable code with no padding or explanation of concepts Claude already knows; every section earns its place.	3 / 3
Actionability	Provides complete, copy-paste-ready code including JWT auth, the POST request, and a polling loop, plus concrete parameter and error tables.	3 / 3
Workflow Clarity	The basic example sequences auth → submit → poll → handle succeed/failed with an explicit status feedback loop, and error/mutual-exclusivity tables guide recovery.	3 / 3
Progressive Disclosure	Sections are organized, but the body inlines full API reference and multiple advanced examples while the five existing references/ files (e.g. motion-control-options.md, batch-image-processing.md) are never signaled or linked from the body.	2 / 3
	Total	11 / 12 Passed

Description

100%

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 third-person, concise, and clearly answers both what the skill does and when to use it, with natural trigger phrases. It is a strong example matching the top anchors across all dimensions.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Animate static images into video', 'converting images to video', 'adding motion to stills', and 'building I2V pipelines' — matching the multiple-specific-actions anchor.	3 / 3
Completeness	Explicitly states what it does ('Animate static images into video using Kling AI') and when to use it ('Use when converting images to video...'), with explicit trigger guidance.	3 / 3
Trigger Term Quality	Provides natural trigger phrases a user would say ('klingai image to video', 'kling ai animate image', 'klingai img2vid', 'animate picture klingai'), giving good coverage of common variations.	3 / 3
Distinctiveness Conflict Risk	Kling AI-specific niche with distinctive trigger phrases makes it unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 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

Discovery Implementation Validation

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