klingai-video-extension
Extend video duration using Kling AI continuation. Use when creating longer videos from shorter clips or building sequences. Trigger with phrases like 'klingai extend video', 'kling ai video continuation', 'klingai longer video', 'extend klingai clip'.
79
76%
Does it follow best practices?
Impact
Pending
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-video-extension/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 is well-structured with explicit 'Use when' and 'Trigger with' clauses, making it complete and distinctive. However, the specificity of capabilities could be improved by listing more concrete actions beyond just 'extend video duration', and the trigger terms are overly reliant on the 'klingai' brand prefix rather than natural user language.
Suggestions
Add more specific concrete actions such as 'chain multiple clips into sequences', 'set continuation duration', or 'extend from a specific frame' to improve specificity.
Include more natural, non-branded trigger terms users might say, such as 'make video longer', 'continue this clip', 'video extension', or 'lengthen video' alongside the branded terms.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Kling AI video continuation) and one core action (extend video duration), but doesn't list multiple specific concrete actions like specifying parameters, chaining sequences, or handling different input formats. | 2 / 3 |
Completeness | Clearly answers both 'what' (extend video duration using Kling AI continuation, creating longer videos from shorter clips or building sequences) and 'when' (explicit 'Use when' clause and 'Trigger with phrases' providing concrete trigger terms). | 3 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'extend video', 'video continuation', 'longer video', 'extend clip', but these are heavily branded ('klingai') and miss more natural user phrases like 'make video longer', 'continue video', 'loop video', or 'video extension'. Users may not always prefix with 'klingai'. | 2 / 3 |
Distinctiveness Conflict Risk | The description is clearly scoped to Kling AI video extension/continuation, which is a very specific niche unlikely to conflict with other skills. The branded trigger terms further reduce ambiguity. | 3 / 3 |
Total | 10 / 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 with executable code examples and clear multi-step workflows including proper polling and error handling. The main weakness is moderate verbosity—the basic extension and chaining examples have overlapping patterns that could be consolidated. The progressive disclosure could be improved by moving the advanced chaining example to a separate reference file.
Suggestions
Consolidate the basic extension example and chain_extensions into a single section to reduce redundancy—the basic example's polling logic is repeated in the chain function.
Consider moving the chain_extensions function and 20-second usage example to a separate EXAMPLES.md file, keeping SKILL.md as a leaner overview with just the basic extension pattern.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good use of tables and code, but includes some redundancy—the basic extension example and the chain_extensions function overlap significantly, and the 20-second usage example repeats the initial generation pattern. The parameter table and error handling table are well-structured but the overall content could be tightened. | 2 / 3 |
Actionability | Provides fully executable Python code with complete authentication setup, API calls, polling logic, and chaining. The code is copy-paste ready with specific endpoints, JSON payloads, and response parsing. The parameter table and error handling table provide concrete, specific guidance. | 3 / 3 |
Workflow Clarity | The multi-step process is clearly sequenced (generate initial → poll → extend → poll extension) with explicit validation via polling for task status. Error handling is included with status checks for both 'succeed' and 'failed' states, and the chain_extensions function includes proper error propagation via RuntimeError. | 3 / 3 |
Progressive Disclosure | The content is well-structured with clear sections progressing from basic to advanced usage, and includes external resource links. However, the chain_extensions function and the 20-second usage example could potentially be split into a separate file given the overall length, and the content is somewhat monolithic for a SKILL.md overview. | 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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