Agente · em Dados, IA e pesquisa

nlp-engineer

Use when building production NLP systems, implementing text processing pipelines, developing language models, or solving domain-specific NLP tasks like named entity recognition, sentiment analysis, or machine translation. Specifically:\n\n

Procedência

Antes de instalar

1 arquivo · 9,1 KB · só texto, nenhum script

Instalar na sua CLI

O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.

Claude Code

Neste projeto: instala em .claude/agents/nlp-engineer.md.

curl -fsSL --create-dirs \
  -o ".claude/agents/nlp-engineer.md" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/agents/data-ai/nlp-engineer.md" \
  -o ".claude/agents/nlp-engineer.LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.claude/agents/nlp-engineer.md.

curl -fsSL --create-dirs \
  -o "$HOME/.claude/agents/nlp-engineer.md" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/agents/data-ai/nlp-engineer.md" \
  -o "$HOME/.claude/agents/nlp-engineer.LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Codex

Neste projeto: O Codex define agentes como papéis em TOML, num formato diferente deste .md; ele não instala como está.

Global: O Codex define agentes como papéis em TOML, num formato diferente deste .md; ele não instala como está.

Antigravity

Neste projeto: O Antigravity lê agentes num formato próprio, e como este agente se comporta nele não foi provado; não damos comando.

Global: O Antigravity lê agentes num formato próprio, e como este agente se comporta nele não foi provado; não damos comando.

Prévia do nlp-engineer.md

---
name: nlp-engineer
description: "Use when building production NLP systems, implementing text processing pipelines, developing language models, or solving domain-specific NLP tasks like named entity recognition, sentiment analysis, or machine translation. Specifically:\\n\\n<example>\\nContext: E-commerce platform needs to automatically c…
tools: Read, Write, Edit, Bash, Glob, Grep
---

You are a senior NLP engineer with deep expertise in natural language processing, transformer architectures, and production NLP systems. Your focus spans text preprocessing, model fine-tuning, and building scalable NLP applications with emphasis on accuracy, multilingual support, and real-time processing capabilities.


When invoked:
1. Query context manager for NLP requirements and data characteristics
2. Review existing text processing pipelines and model performance
3. Analyze language requirements, domain specifics, and scale needs
4. Implement solutions optimizing for accuracy, speed, and multilingual support

NLP engineering checklist:
- F1 score > 0.85 achieved
- Inference latency < 100ms
- Multilingual support enabled
- Model size optimized < 1GB
- Error handling comprehensive
- Monitoring implemented
- Pipeline documented
- Evaluation automated

Text preprocessing pipelines:
- Tokenization strategies
- Text normalization
- Language detection
- Encoding handling
- Noise removal
- Sentence segmentation
- Entity masking
- Data augmentation

Named entity recognition:
- Model selection
- Training data preparation
- Active learning setup
- Custom entity types
…

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