klingai-cost-controls
Implement budget limits, usage alerts, and spending controls for Kling AI. Use when managing costs or preventing overruns. Trigger with phrases like 'klingai cost', 'kling ai budget', 'klingai spending limit', 'video generation costs'.
64
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/klingai-pack/skills/klingai-cost-controls/SKILL.mdQuality
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 solid skill description that clearly identifies its niche (cost management for Kling AI), provides explicit trigger terms, and answers both what and when. The main weakness is that the capability actions could be more specific—listing concrete operations rather than general categories like 'budget limits' and 'spending controls'.
Suggestions
Make capabilities more concrete by specifying exact actions, e.g., 'Set daily/monthly spending caps, configure usage threshold alerts, track per-video generation costs, and pause generation when budgets are exceeded.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Kling AI budget management) and some actions ('budget limits, usage alerts, spending controls'), but these are somewhat generic financial management terms rather than deeply specific concrete actions like 'set daily spending caps' or 'configure email alerts at threshold percentages'. | 2 / 3 |
Completeness | Clearly answers both 'what' (implement budget limits, usage alerts, spending controls for Kling AI) and 'when' (managing costs, preventing overruns) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes good natural trigger terms: 'klingai cost', 'kling ai budget', 'klingai spending limit', 'video generation costs'. These cover variations of the product name and common cost-related phrases a user would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific product name 'Kling AI' combined with cost/budget management. Unlikely to conflict with other skills unless there are multiple Kling AI skills, and even then the budget/cost focus narrows it well. | 3 / 3 |
Total | 11 / 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 highly actionable, executable Python code for Kling AI cost controls with useful credit reference tables and optimization strategies. Its main weaknesses are the lack of an explicit end-to-end workflow showing how all components connect, and the somewhat verbose code that could be tightened or split into supporting files. The content is well-structured but would benefit from a clear integration example and better progressive disclosure.
Suggestions
Add a brief 'Quick Start' or 'Integration Workflow' section at the top showing the end-to-end sequence: initialize BudgetGuard → wrap with CostAwareKlingClient → pre-batch check → generate → log with UsageTracker.
Consider moving the full class implementations (BudgetGuard, UsageTracker) into a referenced support file and keeping only the key API surface and usage examples inline in SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with useful code and tables, but the code is quite lengthy and some patterns (like the UsageTracker class) are straightforward enough that Claude could generate them without detailed guidance. The credit cost reference table and optimization strategies table are high-value, but the full class implementations could be more concise. | 2 / 3 |
Actionability | All code is fully executable Python with concrete classes, methods, and clear usage patterns. The BudgetGuard, CostAwareKlingClient, pre_batch_check, and UsageTracker are all copy-paste ready with specific credit values and real configuration parameters. | 3 / 3 |
Workflow Clarity | The components are well-defined individually but there's no explicit end-to-end workflow showing how to wire them together (e.g., create BudgetGuard → wrap client → run pre-batch check → generate → log). The pre-batch check includes a validation step with error recovery guidance, but there's no overall sequenced workflow with checkpoints for the full cost-controlled generation pipeline. | 2 / 3 |
Progressive Disclosure | The content is well-sectioned with clear headers and a logical progression from reference data to implementation to optimization. However, given the length (~150+ lines of code), some components like the full UsageTracker or BudgetGuard could be split into referenced files. The external resource links at the end are helpful but minimal. | 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 | |
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