klingai-storage-integration
Download and store Kling AI generated videos in cloud storage (S3, GCS, Azure). Use when persisting videos or building CDN pipelines. Trigger with phrases like 'klingai storage', 'save klingai video', 'kling ai s3 upload', 'klingai cloud storage'.
67
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
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.
This is a well-crafted skill description that clearly defines its niche at the intersection of Kling AI video generation and cloud storage. It provides specific capabilities, explicit trigger phrases, and clear usage guidance. The description is concise yet comprehensive, covering the what, when, and how-to-trigger aspects effectively.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Download and store Kling AI generated videos in cloud storage' with explicit platforms '(S3, GCS, Azure)' and mentions 'CDN pipelines'. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (download and store Kling AI videos in cloud storage) and 'when' (use when persisting videos or building CDN pipelines), with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases like 'klingai storage', 'save klingai video', 'kling ai s3 upload', 'klingai cloud storage' which cover multiple variations a user might say. Also includes cloud provider names (S3, GCS, Azure) as natural keywords. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche combining Kling AI video generation with cloud storage operations. The specific combination of 'Kling AI' + 'cloud storage' makes it very unlikely to conflict with generic video or storage skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides solid, actionable code for downloading Kling AI videos and uploading to three major cloud providers. Its main weaknesses are the lack of validation/error-handling checkpoints in the workflow (plus a bug where cleanup never executes), and the monolithic structure that could benefit from splitting provider-specific code into separate files. The content is reasonably concise but could be tightened by removing redundant patterns across providers.
Suggestions
Add validation checkpoints: verify download file size > 0, confirm upload success with a HEAD request or equivalent, and wrap operations in try/except with meaningful error messages.
Fix the end-to-end pipeline bug where `os.remove(filepath)` at step 5 is unreachable because it follows a return statement — use a try/finally block instead.
Consider splitting provider-specific upload functions into separate referenced files (e.g., s3_upload.md, gcs_upload.md, azure_upload.md) to reduce the main skill's token footprint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with executable code, but includes some unnecessary elements like print statements, docstrings explaining obvious behavior, and the metadata preservation section adds bulk. The three cloud provider sections are repetitive in structure, though each provides distinct value. | 2 / 3 |
Actionability | All code examples are fully executable with proper imports, concrete function signatures, and copy-paste ready implementations. The end-to-end pipeline ties everything together with a clear multi-provider pattern. | 3 / 3 |
Workflow Clarity | The end-to-end pipeline has a clear numbered sequence (generate → poll → download → upload → cleanup), but lacks validation checkpoints — no verification that the download succeeded, no file integrity check, no confirmation the upload completed successfully. The cleanup step at #5 executes after the return statement and would never run, which is a bug. | 2 / 3 |
Progressive Disclosure | The content is well-sectioned with clear headers, but it's a monolithic file with ~130 lines of code that could benefit from splitting provider-specific uploads into separate files. The Resources section provides external links but there are no bundle files to offload detailed content. | 2 / 3 |
Total | 9 / 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
a04d1a2
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.