Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsnpx agentmods add skills/ricneves-ai/flowgrammers-skills/senior-data-engineerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/senior-data-engineer)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/senior-data-engineer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/senior-data-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/senior-data-engineer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/senior-data-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.01725 |
| Opus 5 | $0.00054 | $0.00863 |
| Sonnet 5 | $0.00022 | $0.00345 |
| Haiku 4.5 | $0.00011 | $0.00172 |
Grade A, and why
senior-data-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engenheiro de Dados Sênior
Skill de engenharia de dados em nível de produção para construção de sistemas de dados escaláveis e confiáveis.
Sumário
- Frases de Gatilho
- Início Rápido
- Fluxos de Trabalho
- Framework de Decisão de Arquitetura
- Tech Stack
- Documentação de Referência
- Solução de Problemas
Frases de Gatilho
Ative esta skill quando ver:
Design de Pipeline:
- "Projetar um pipeline de dados para..."
- "Construir um processo ETL/ELT..."
- "Como ingerir dados de..."
- "Configurar extração de dados de..."
Arquitetura:
- "Devo usar batch ou streaming?"
- "Arquitetura Lambda vs Kappa"
- "Como lidar com dados de chegada tardia"
- "Projetar um data lakehouse"
Modelagem de Dados:
- "Criar um modelo dimensional..."
- "Star schema vs snowflake"
- "Implementar slowly changing dimensions"
- "Projetar um data vault"
Qualidade de Dados:
- "Adicionar validação de dados a..."
- "Configurar verificações de qualidade de dados"
- "Monitorar frescor dos dados"
- "Implementar contratos de dados"
Desempenho:
- "Otimizar este job Spark"
- "Query está rodando lenta"
- "Reduzir tempo de execução do pipeline"
- "Ajustar DAG do Airflow"
Início Rápido
Ferramentas Principais
# Gerar configuração de orquestração de pipeline
python scripts/pipeline_orchestrator.py generate \
--type airflow \
--source postgres \
--destination snowflake \
--schedule "0 5 * * *"
# Validar qualidade de dados
python scripts/data_quality_validator.py validate \
--input data/sales.parquet \
--schema schemas/sales.json \
--checks freshness,completeness,uniqueness
# Otimizar desempenho ETL
python scripts/etl_performance_optimizer.py analyze \
--query queries/daily_aggregation.sql \
--engine spark \
--recommend
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 196 lines · 108 tokens per session scan A 53877151a4a1
senior-data-engineer is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It adds 108 tokens to every session and 1,725 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
gemini-api-agent-platform
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK for enterprise AI applications. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
open-source
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browseruse, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle…
gemini-api-dev
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best…
deepstream-sop
Use this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the…
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…
coral-create-source-spec
Create or update a Coral source spec YAML for a custom HTTP API or local dataset. Use when authoring a standalone source for coral source add --file, or when adapting that spec into a Coral repo source under sources/core or sources/community.