Skill para desenhar e implementar integracoes de IA em aplicacoes, separando provider, adapter, hooks, observabilidade, custo e seguranca. Use quando o usuario quiser adicionar texto, imagem ou video ao app. Trigger em: "integrar IA no app", "AI integration", "provider adapter de IA", "feature de IA", "chamar OpenAI", "chamar Anthropic", "Claude API", "LLM no app", "arquitetura de IA", "custo de IA", "fallback de provider", "rate limit de IA".
52
56%
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 ./skills/25-ai-integration-architect/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 with excellent trigger term coverage and clear completeness, explicitly stating both what the skill does and when to use it. The main weakness is that the capability description could be more specific about concrete actions/deliverables rather than listing architectural concerns at a high level. The bilingual trigger terms are a strength for discoverability.
Suggestions
Add more specific concrete actions beyond 'desenhar e implementar', such as 'create provider abstraction layers, implement fallback logic between providers, add usage tracking and cost monitoring'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (AI integrations in applications) and lists architectural concerns like provider, adapter, hooks, observability, cost, and security. However, the concrete actions are somewhat vague — 'desenhar e implementar integracoes' is broad, and it doesn't list specific deliverables like 'create provider abstraction layer' or 'implement fallback logic'. | 2 / 3 |
Completeness | The description clearly answers both 'what' (design and implement AI integrations covering provider, adapter, hooks, observability, cost, security) and 'when' (explicit 'Use quando' clause plus a detailed 'Trigger em' list with specific phrases). Both dimensions are explicitly addressed. | 3 / 3 |
Trigger Term Quality | The description includes an extensive list of natural trigger terms covering multiple variations users would actually say: 'integrar IA no app', 'chamar OpenAI', 'chamar Anthropic', 'Claude API', 'LLM no app', 'fallback de provider', 'rate limit de IA', and bilingual terms (Portuguese and English). This provides excellent keyword coverage. | 3 / 3 |
Distinctiveness Conflict Risk | The skill has a clear niche — AI provider integration architecture with specific concerns like adapter patterns, fallback, rate limiting, and cost. The trigger terms are highly specific to this domain (e.g., 'provider adapter de IA', 'fallback de provider') and unlikely to conflict with general coding or other 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 functions primarily as a routing document that points to external pattern files and policies, but provides almost no actionable content of its own. It lacks concrete code examples, executable guidance, adapter patterns, or a clear step-by-step workflow. While the progressive disclosure structure is reasonable in concept, the skill body itself offers little value without the referenced files.
Suggestions
Add a concrete, step-by-step workflow (e.g., 1. Identify modality → 2. Select provider → 3. Implement adapter → 4. Add hooks → 5. Validate cost/security → 6. Handoff) with explicit validation checkpoints at each stage.
Include at least one executable code example showing a minimal provider adapter pattern (e.g., a TypeScript/Python adapter interface with a concrete OpenAI or Anthropic implementation).
Replace the abstract 'Entradas Esperadas' and 'Saidas Esperadas' sections with a concrete example: given a specific use case, show the expected architecture output (e.g., a diagram or structured plan).
Trim the Governanca Global section to a single reference line rather than listing every policy file individually.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is moderately efficient but includes several sections that are somewhat boilerplate (Governanca Global listing many policy files, Quando Usar/Nao Usar, Entradas/Saidas Esperadas) without adding much actionable value. The submodule section at the end is useful but could be tighter. | 2 / 3 |
Actionability | The skill provides no concrete code, no executable examples, no specific adapter patterns, no API call examples, and no schemas. It entirely delegates to external pattern files (patterns/ai-integration/*) without showing any actual implementation guidance. It describes what to do abstractly rather than instructing concretely. | 1 / 3 |
Workflow Clarity | There is no clear sequenced workflow for performing an AI integration. The skill lists inputs, outputs, and references to consult, but never defines a step-by-step process with validation checkpoints. For a multi-step architectural task involving provider selection, adapter implementation, cost/security review, and handoff, the absence of a sequenced workflow is a significant gap. | 1 / 3 |
Progressive Disclosure | The skill references multiple external pattern files and policies with clear paths, which is good structure. However, since no bundle files are provided, we cannot verify these references exist. The skill itself is essentially just a pointer to other files with very little standalone value, which tips it toward being an empty shell rather than a well-structured 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.
7577622
Table of Contents
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