klingai-install-auth
Set up Kling AI API authentication with JWT tokens. Use when starting a new Kling AI integration or troubleshooting auth issues. Trigger with phrases like 'kling ai setup', 'klingai api key', 'kling ai authentication', 'configure klingai'.
68
83%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
89%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-structured skill description with clear 'what' and 'when' clauses, explicit trigger phrases, and a distinct niche. Its main weakness is that the capability description could be more specific about what concrete actions it performs beyond 'set up authentication' (e.g., generating JWT tokens, configuring API keys, handling token refresh). Overall it's a strong description that would perform well in skill selection.
Suggestions
Expand the capability list with more specific actions, e.g., 'Generate JWT tokens, configure API credentials, handle token refresh, and resolve common authentication errors for Kling AI API.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Kling AI API) and a specific action (JWT token authentication setup), but doesn't list multiple concrete actions beyond setup and troubleshooting. It's more than vague but not comprehensively listing specific capabilities. | 2 / 3 |
Completeness | Clearly answers both 'what' (set up Kling AI API authentication with JWT tokens) and 'when' (starting a new Kling AI integration or troubleshooting auth issues), with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes multiple natural trigger phrases users would say: 'kling ai setup', 'klingai api key', 'kling ai authentication', 'configure klingai'. Good coverage of variations including both 'kling ai' and 'klingai' spellings. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting Kling AI API authentication specifically. The combination of 'Kling AI', 'JWT tokens', and 'API authentication' makes it highly unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill for Kling AI authentication setup with executable code in two languages, clear step sequencing, and good error handling guidance. Its main weakness is moderate verbosity—explaining JWT concepts Claude already knows and including generic security advice that doesn't add value. The workflow is well-structured with an explicit verification step.
Suggestions
Remove the JWT explanation in the Overview ('Kling AI uses JWT...') and generic security advice (never commit secrets, use .gitignore) that Claude already knows—just keep Kling-specific constraints like the 1800s max expiry.
Consider trimming the Node.js example if the skill's primary audience is Python-focused, or move it to a separate reference file to reduce the main skill's token footprint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient but includes some unnecessary elements. The overview explains what JWT is and how it works, which Claude already knows. The Token Management Pattern section, while useful, adds significant length. The security checklist contains generic advice (never commit secrets, use .gitignore) that Claude already knows. | 2 / 3 |
Actionability | Excellent actionability with fully executable Python and Node.js code examples, specific URLs for credential setup, concrete .env file format, a complete auto-refreshing token manager class, and a verification step with specific status code handling. All code is copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear 3-step sequence (Get Credentials → Generate JWT → Verify Authentication) with an explicit verification step that checks status codes and provides diagnostic output. The error handling table serves as a troubleshooting feedback loop, and the token management pattern addresses the token expiry lifecycle. | 3 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and headers, but it's somewhat monolithic for its length (~120 lines of substantive content). The Token Management Pattern and Error Handling sections could potentially be split into separate reference files. However, with no bundle files provided, the inline approach is reasonable for a single-purpose auth skill. | 2 / 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 | |
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