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.

Quality

56%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/27-video-integration-specialist/SKILL.md

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 solid skill description that clearly identifies its domain (generative video integration) and provides explicit trigger guidance with a 'Use quando...' clause. Its main weakness is that it lists video workflow types rather than concrete actions the skill performs (e.g., 'generates video from text prompts', 'creates avatar-based videos'). The trigger terms are strong and distinctive, making it easy for Claude to select this skill appropriately.

Suggestions

Replace the general phrase 'integrar geracao e manipulacao de video' with specific concrete actions like 'Generates videos from text prompts, converts images to video sequences, creates avatar-based talking head videos, and produces animated motion explainers.'

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 workflows rather than specific actions the skill performs.	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 with specific triggers.	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 distinct triggers like text-to-video, image-to-video, avatar video, and motion explainers. These are unlikely to conflict with other skills such as image generation or video editing/playback skills.	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 as a metadata/routing document rather than an actionable skill. It defines when to use the skill, what inputs/outputs to expect, and which files to consult, but provides zero concrete technical guidance on how to actually integrate video generation. The complete absence of code examples, API patterns, workflow steps, or specific implementation details makes it nearly unusable as a standalone skill.

Suggestions

Add a concrete workflow with numbered steps showing the actual integration process (e.g., 1. Choose provider, 2. Implement adapter pattern, 3. Set up async processing, 4. Handle webhook callbacks, 5. Validate output), including validation checkpoints.

Include at least one executable code example showing a video generation adapter pattern (e.g., a provider adapter interface, an API call to a video generation service like Runway or Pika, or a webhook handler).

Replace the abstract 'Saidas Esperadas' section with a concrete example of what an integration plan looks like — even a minimal template with specific fields and sample values.

Add brief descriptions next to each referenced file so readers know what they'll find (e.g., 'video-generation.md — provider comparison table, adapter interfaces, async polling patterns').

Dimension	Reasoning	Score
Conciseness	The skill is relatively short but contains several sections that are boilerplate/organizational overhead (Governanca Global, Quando Usar/Nao Usar, Entradas/Saidas Esperadas) without providing concrete technical value. Some sections like 'Evidencia de Conclusao' are thin checklists that don't add much actionable content.	2 / 3
Actionability	The skill provides no concrete code, commands, API examples, or executable guidance. It describes what should happen at a high level (e.g., 'adapter, hook e fluxo de processamento recomendados') but never shows how. There are no code snippets, no API call examples, no configuration samples — everything is abstract direction.	1 / 3
Workflow Clarity	There is no sequenced workflow or multi-step process defined. The skill lists inputs, outputs, and references but never describes the actual steps to integrate video generation into an app. No validation checkpoints or feedback loops are present for what is inherently a multi-step integration process.	1 / 3
Progressive Disclosure	The skill references multiple external files (patterns/ai-integration/video-generation.md, policies/handoffs.md, etc.) which shows some progressive disclosure structure. However, the references are not clearly signaled with descriptions of what each contains, and the main file itself has almost no substantive content — it's essentially just a routing document to other files.	2 / 3
	Total	6 / 12 Passed

Validation

100%

Warnings & errors only

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: d87ad31

Reviewed: 15 days ago

Table of Contents

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