video-integration-specialist
Skill para integrar geracao e manipulacao de video em aplicacoes. Use quando o app precisar de text-to-video, image-to-video, clips promocionais, avatar video, motion explainers ou outros fluxos de video generativo.
65
56%
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 ./skills/27-video-integration-specialist/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 domain (generative video integration) and provides explicit trigger guidance with a 'Use quando...' clause. The main weakness is that it lists video content types rather than concrete actions/operations the skill performs (e.g., generate, render, export, configure). The trigger terms are strong and distinctive.
Suggestions
Replace or supplement the content-type list with concrete action verbs describing what the skill does (e.g., 'Generates videos from text prompts, converts images to video sequences, renders promotional clips, creates avatar-based videos').
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (video generation/manipulation) and lists several specific use cases like text-to-video, image-to-video, clips promocionais, avatar video, motion explainers, but doesn't describe concrete actions (e.g., 'generates', 'renders', 'exports'). It lists types of video content rather than specific operations. | 2 / 3 |
Completeness | Clearly answers both 'what' (integrar geracao e manipulacao de video em aplicacoes) and 'when' (Use quando o app precisar de text-to-video, image-to-video, clips promocionais, avatar video, motion explainers ou outros fluxos de video generativo). Has an explicit 'Use quando...' clause. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'text-to-video', 'image-to-video', 'clips promocionais', 'avatar video', 'motion explainers', 'video generativo'. These are terms users would naturally use when requesting video generation capabilities. | 3 / 3 |
Distinctiveness Conflict Risk | The description carves out a clear niche around generative video workflows with specific trigger terms like text-to-video, image-to-video, avatar video, and motion explainers. This is unlikely to conflict with other skills like general video editing or image generation. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
22%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a role charter or task routing document than an actionable skill. It defines when to use the skill and what outputs to produce, but provides zero concrete guidance on how to actually integrate video generation — no code examples, no API patterns, no workflow steps, no prompt templates. The heavy reliance on external references without any substantive content in the skill itself means Claude would need to read multiple other files before having any actionable information.
Suggestions
Add a concrete workflow with numbered steps showing the actual integration process (e.g., 1. Select provider, 2. Implement adapter pattern, 3. Set up async processing, 4. Handle status polling, 5. Validate output), including validation checkpoints.
Include at least one executable code example showing a video generation adapter pattern or API integration (e.g., a provider adapter interface, a webhook handler for async video completion, or a React hook for video status polling).
Add a concrete prompt engineering example for cinematographic prompts — show an input scenario and the expected structured prompt output that would be sent to a video generation API.
Replace the generic 'Entradas Esperadas' and 'Saidas Esperadas' lists with a concrete example scenario (e.g., 'Given: promotional clip feature using Runway ML, 5s duration, <$0.50/clip → Here's the integration plan...').
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is relatively brief but contains several sections that are somewhat boilerplate and don't add much actionable value (e.g., 'Quando Usar', 'Quando Nao Usar' lists are generic). It avoids explaining concepts Claude already knows, but the structure feels padded with organizational ceremony rather than substance. | 2 / 3 |
Actionability | The skill provides no concrete code, commands, API examples, or executable guidance. It describes what should happen at a high level ('definir status, processamento, custo') but never shows how — no adapter patterns, no hook implementations, no API call examples, no prompt templates. It reads as a role description rather than actionable instructions. | 1 / 3 |
Workflow Clarity | There is no sequenced workflow, no numbered steps, and no validation checkpoints. The skill lists inputs, outputs, and references but never describes the actual process of integrating video generation. For a multi-step integration task involving providers, adapters, and processing flows, the absence of any workflow sequence is a significant gap. | 1 / 3 |
Progressive Disclosure | The skill references external files (patterns/ai-integration/video-generation.md, policies/handoffs.md, etc.) which is good progressive disclosure structure. However, the references are numerous and not clearly signaled with descriptions of what each contains, making navigation harder. The main file itself lacks enough substance to serve as a useful overview. | 2 / 3 |
Total | 6 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- felvieira/claude-skills-fv
- Commit
e9f6648
- Reviewed
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