klingai-style-transfer
Apply artistic styles and visual effects to Kling AI video generation. Use when creating stylized content or using effects API. Trigger with phrases like 'klingai style', 'kling ai effects', 'klingai artistic video', 'stylize klingai video'.
77
73%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/klingai-pack/skills/klingai-style-transfer/SKILL.mdQuality
Discovery
75%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 adequately identifies its niche (Kling AI artistic styles/effects) and provides both 'what' and 'when' clauses with explicit triggers. However, it lacks specificity in the concrete actions it performs and the trigger terms feel somewhat manufactured rather than reflecting natural user language. The description would benefit from listing specific capabilities and more natural keyword variations.
Suggestions
Add specific concrete actions such as 'apply preset art styles, configure visual effects parameters, combine multiple effects, preview stylized outputs'.
Include more natural trigger term variations users would actually say, such as 'video style transfer', 'artistic video generation', 'add effects to video', 'stylized video', or 'Kling effects API'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Kling AI video generation) and mentions 'artistic styles and visual effects' but doesn't list specific concrete actions like applying particular style types, configuring effect parameters, or generating previews. | 2 / 3 |
Completeness | Clearly answers both 'what' (apply artistic styles and visual effects to Kling AI video generation) and 'when' (when creating stylized content or using effects API), with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes some relevant trigger phrases like 'klingai style', 'kling ai effects', 'klingai artistic video', 'stylize klingai video', but these feel somewhat artificial and formulaic rather than natural user language. Missing common variations like 'video style transfer', 'artistic video', or 'visual effects on video'. | 2 / 3 |
Distinctiveness Conflict Risk | The description is clearly scoped to Kling AI's specific style/effects functionality, making it highly distinguishable from general video generation or other AI platform skills. The 'klingai' prefix in trigger terms further reduces conflict risk. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, highly actionable skill with executable code examples and useful reference tables for style prompts and effects. Its main weakness is the lack of validation/error handling in workflows — polling for task completion is hand-waved, and there's no guidance on handling failures or verifying output quality. The cfg_scale information could be consolidated to reduce minor redundancy.
Suggestions
Add a concrete polling implementation with error handling (check task status, handle failures, timeout) rather than just commenting 'Poll for result as usual'
Consolidate the cfg_scale guidance — the tuning table and the style transfer recommendation could be merged into a single section to reduce redundancy
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with useful tables and code examples, but there's some redundancy (e.g., the auth helper is shown once and reused well, but the cfg_scale information is explained in both the table and a separate section). The style prompt recipes table is a good density format, though the overall document is fairly long. | 2 / 3 |
Actionability | Fully executable Python code examples throughout, including authentication setup, text-to-video with style prompts, Effects API usage, Kolors restyle pipeline, and a reusable style template function. All examples are copy-paste ready with specific endpoints, parameters, and JSON payloads. | 3 / 3 |
Workflow Clarity | The Kolors restyle section shows a clear two-step workflow (generate image → use as I2V input), and the style consistency section provides a reusable pattern. However, there are no validation checkpoints — no error handling for API responses, no polling implementation shown (just a comment 'Poll for result as usual'), and no verification that generated content matches the intended style. | 2 / 3 |
Progressive Disclosure | Content is well-organized into logical sections (prompt engineering, effects API, Kolors, cfg_scale tuning, consistency patterns) with clear headers. External resources are linked at the bottom for deeper API documentation. The length is appropriate for inline content without needing separate files. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 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 | 9 / 11 Passed | |
- Commit
70e9fa4
- Reviewed
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