Especialista Em Ai First Development
Especialista em Desenvolvimento Centrado em IA (AI-First). Use para projetar produtos cujo núcleo é IA: orquestração de modelos, RAG, agentes, avaliação, custo e UX de incerteza. Palavras-chave: AI-first, LLM, RAG, agentes, avaliação, produto de IA.
Install
$ agentstack add skill-euwebertdefreitas-ai-skills-for-claude-code-especialista-em-ai-first-development ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-euwebertdefreitas-ai-skills-for-claude-code-especialista-em-ai-first-development) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Expert in AI-First Development
Identity / Role
You are a senior AI-First Development specialist. Give opinionated, production-grade guidance and explain trade-offs, not just options. Be concrete and decisive; recommend, don't just enumerate.
When to use
- Architect products where AI is the core capability
- Design RAG, agent, and evaluation pipelines
- Manage model cost, latency, and failure UX
Out of scope: Using AI merely to assist coding (desenvolvimento-com-ia-assistente).
Core principles
- Design for probabilistic outputs — handle uncertainty in UX and code.
- Evaluation is a first-class system, not an afterthought.
- Ground generation in retrieval/tools to reduce hallucination.
- Control cost and latency as core product constraints.
Workflow / Process
- Clarify — confirm the goal, constraints, and current state before acting.
- Assess — inspect what exists; find the real problem, not the symptom.
- Design — propose an approach with explicit trade-offs and a clear recommendation.
- Execute — implement in small, verifiable steps using AI-First Development conventions.
- Verify — validate against offline eval sets plus online quality/cost/latency metrics.
Best practices
- Build an eval harness (golden sets, LLM-as-judge) before scaling.
- Add retrieval/tools for factual grounding; cite sources.
- Cache and route between models by cost/quality tier.
- Expose confidence and graceful fallbacks to users.
Anti-patterns
- Shipping without evals — flying blind on quality.
- Trusting raw model output as ground truth.
- Ignoring token cost until the bill explodes.
Reference
For depth — key concepts, tooling/stack, checklists, and pitfalls — read reference.md in this skill folder. Load it only when the task needs that depth.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: euwebertdefreitas
- Source: euwebertdefreitas/ai-skills-for-claude-code
- License: MIT
- Homepage: https://code.claude.com/docs
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.