How do I install the Luanmorenommaciel Agentspec Agentspec skill?

Run npx skillmds@latest add tomevault-io/luanmorenommaciel-agentspec-agentspec in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Luanmorenommaciel Agentspec Agentspec skill do?

Data Engineering Guide It is listed under Coding & Dev Tools on SkillMD.

Is Luanmorenommaciel Agentspec Agentspec safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Luanmorenommaciel Agentspec Agentspec?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Luanmorenommaciel Agentspec Agentspec free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Luanmorenommaciel Agentspec Agentspec?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Luanmorenommaciel Agentspec Agentspec by tomevault-io

Name: Luanmorenommaciel Agentspec Agentspec
Author: tomevault-io

File contents

Data Engineering Guide

You have access to 23 specialized knowledge base domains and 15+ data engineering agents. Route the user to the right tool based on their task.

Quick Routing

User Task	Command	Agent
Design a data pipeline / DAG	`/agentspec:pipeline`	pipeline-architect
Design a schema / star schema / data model	`/agentspec:schema`	schema-designer
Add data quality checks	`/agentspec:data-quality`	data-quality-analyst
Review SQL performance	`/agentspec:sql-review`	sql-optimizer
Choose table format (Iceberg/Delta)	`/agentspec:lakehouse`	lakehouse-architect
Build RAG / embedding pipeline	`/agentspec:ai-pipeline`	ai-data-engineer
Create a data contract	`/agentspec:data-contract`	data-contracts-engineer
Migrate legacy ETL	`/agentspec:migrate`	dbt-specialist + spark-engineer

Knowledge Domains Available

Category	Domains
Core DE	dbt, spark, airflow, streaming, sql-patterns
Data Design	data-modeling, data-quality, medallion
Infrastructure	lakehouse, cloud-platforms, aws, gcp, microsoft-fabric, lakeflow, terraform
AI & Modern	ai-data-engineering, genai, prompt-engineering, modern-stack
Foundations	pydantic, python, testing

How Agents Use Knowledge

Agent reads KB index at ${CLAUDE_PLUGIN_ROOT}/kb/{domain}/index.md
Loads specific pattern/concept file matching the task
Falls back to MCP if KB insufficient (max 3 MCP calls)
Calculates confidence from evidence matrix

When to Suggest Commands

User mentions "dbt model" or "staging model" → /agentspec:schema or delegate to dbt-specialist
User mentions "pipeline" or "DAG" or "orchestration" → /agentspec:pipeline
User mentions "data quality" or "expectations" or "tests" → /agentspec:data-quality
User mentions "slow query" or "optimize SQL" → /agentspec:sql-review
User mentions "Iceberg" or "Delta Lake" or "table format" → /agentspec:lakehouse
User mentions "RAG" or "embeddings" or "vector" → /agentspec:ai-pipeline
User mentions "contract" or "SLA" or "schema governance" → /agentspec:data-contract
User mentions "migrate" or "legacy" or "SSIS" or "Informatica" → /agentspec:migrate

Source: luanmorenommaciel/agentspec — distributed by TomeVault.

---name: luanmorenommaciel-agentspec-agentspecdescription: Data Engineering Guide---# Data Engineering GuideYou have access to 23 specialized knowledge base domains and 15+ data engineering agents. Route the user to the right tool based on their task.## Quick Routing| User Task | Command | Agent ||-----------|---------|-------|| Design a data pipeline / DAG | `/agentspec:pipeline` | pipeline-architect || Design a schema / star schema / data model | `/agentspec:schema` | schema-designer || Add data quality checks | `/agentspec:data-quality` | data-quality-analyst || Review SQL performance | `/agentspec:sql-review` | sql-optimizer || Choose table format (Iceberg/Delta) | `/agentspec:lakehouse` | lakehouse-architect || Build RAG / embedding pipeline | `/agentspec:ai-pipeline` | ai-data-engineer || Create a data contract | `/agentspec:data-contract` | data-contracts-engineer || Migrate legacy ETL | `/agentspec:migrate` | dbt-specialist + spark-engineer |## Knowledge Domains Available| Category | Domains ||----------|---------|| Core DE | dbt, spark, airflow, streaming, sql-patterns || Data Design | data-modeling, data-quality, medallion || Infrastructure | lakehouse, cloud-platforms, aws, gcp, microsoft-fabric, lakeflow, terraform || AI & Modern | ai-data-engineering, genai, prompt-engineering, modern-stack || Foundations | pydantic, python, testing |## How Agents Use Knowledge1. Agent reads KB index at `${CLAUDE_PLUGIN_ROOT}/kb/{domain}/index.md`2. Loads specific pattern/concept file matching the task3. Falls back to MCP if KB insufficient (max 3 MCP calls)4. Calculates confidence from evidence matrix## When to Suggest Commands- User mentions "dbt model" or "staging model" → `/agentspec:schema` or delegate to dbt-specialist- User mentions "pipeline" or "DAG" or "orchestration" → `/agentspec:pipeline`- User mentions "data quality" or "expectations" or "tests" → `/agentspec:data-quality`- User mentions "slow query" or "optimize SQL" → `/agentspec:sql-review`- User mentions "Iceberg" or "Delta Lake" or "table format" → `/agentspec:lakehouse`- User mentions "RAG" or "embeddings" or "vector" → `/agentspec:ai-pipeline`- User mentions "contract" or "SLA" or "schema governance" → `/agentspec:data-contract`- User mentions "migrate" or "legacy" or "SSIS" or "Informatica" → `/agentspec:migrate`---> Source: [luanmorenommaciel/agentspec](https://github.com/luanmorenommaciel/agentspec) — distributed by [TomeVault](https://tomevault.io).

Frequently asked questions

Luanmorenommaciel Agentspec Agentspec