klingai-usage-analytics
tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill klingai-usage-analyticsBuild usage analytics and reporting for Kling AI. Use when tracking generation patterns, analyzing costs, or creating dashboards. Trigger with phrases like 'klingai analytics', 'kling ai usage report', 'klingai metrics', 'video generation stats'.
Validation
81%| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 13 / 16 Passed | |
Implementation
22%This skill content is essentially a skeleton outline that lacks any concrete, actionable guidance. It lists high-level steps without providing the actual implementation details, code examples, or specific commands needed to build analytics. The content relies entirely on external references for substance while the main file provides almost no executable value.
Suggestions
Add concrete, executable Python code examples for collecting usage data and calculating metrics (e.g., API calls to fetch usage, pandas aggregation code)
Replace vague steps like 'Capture usage events' with specific implementation details including actual API endpoints, data structures, and code snippets
Include at least one complete, copy-paste ready example workflow showing data collection through visualization
Add validation checkpoints such as 'Verify data completeness before aggregation' with specific checks to perform
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is relatively brief but includes some unnecessary padding like 'This skill shows how to build comprehensive usage analytics' and generic prerequisites. Could be tighter while maintaining clarity. | 2 / 3 |
Actionability | Provides only vague, abstract steps like 'Collect Data: Capture usage events' with no concrete code, commands, or specific implementation details. No executable examples are present in the main content. | 1 / 3 |
Workflow Clarity | Steps are listed but extremely vague with no actual sequence details, no validation checkpoints, and no guidance on how to perform each step. 'Capture usage events' and 'Calculate key metrics' provide no actionable workflow. | 1 / 3 |
Progressive Disclosure | References external files for errors and examples which is appropriate, but the main content is too sparse to serve as a useful overview. The skill offloads too much to external files without providing sufficient standalone value. | 2 / 3 |
Total | 6 / 12 Passed |
Activation
90%This is a solid skill description with excellent trigger term coverage and clear distinctiveness for Kling AI analytics. The main weakness is that the capability descriptions could be more specific about concrete actions beyond the general categories of tracking, analyzing, and creating dashboards.
Suggestions
Add more specific concrete actions like 'generate cost breakdowns by model type', 'export usage reports to CSV', or 'visualize generation trends over time' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Kling AI analytics) and some actions (tracking generation patterns, analyzing costs, creating dashboards), but lacks comprehensive detail about specific concrete actions like 'generate cost breakdowns', 'export CSV reports', or 'visualize generation trends'. | 2 / 3 |
Completeness | Clearly answers both what (build usage analytics and reporting for Kling AI) and when (tracking generation patterns, analyzing costs, creating dashboards) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes good coverage of natural trigger terms users would say: 'klingai analytics', 'kling ai usage report', 'klingai metrics', 'video generation stats'. These are specific, natural phrases that distinguish this skill. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche targeting Kling AI analytics specifically. The trigger terms include the product name variations ('klingai', 'kling ai') making it unlikely to conflict with generic analytics or other video generation tools. | 3 / 3 |
Total | 11 / 12 Passed |
Reviewed
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