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mastra

mastra

github.com/pedronauckAgent workflows647239 installsUpdated 2w ago
Repository

About mastra

A guidance skill for building Mastra AI applications. It directs developers to verify APIs against installed or current documentation before writing agents and workflows.

Key features

  1. 01Version-matched embedded documentation lookup
  2. 02Remote documentation lookup
  3. 03Source and type-definition inspection
  4. 04Common error and migration guidance
  5. 05Agent and workflow development steps

Use cases

  1. 01Checking the API for an installed Mastra version
  2. 02Finding current guidance when Mastra packages are absent
  3. 03Troubleshooting type or constructor errors

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/pedronauck/skills --skill mastra

After installing, type/mastrain Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
common-errors.md
create-mastra.md
embedded-docs.md
migration-guide.md
remote-docs.md

Details

From the project README

Mastra Framework Guide

Build AI applications with Mastra. This skill teaches you how to find current documentation and build agents and workflows.

⚠️ Critical: Do not trust internal knowledge

Everything you know about Mastra is likely outdated or wrong. Never rely on memory. Always verify against current documentation.

Your training data contains obsolete APIs, deprecated patterns, and incorrect usage. Mastra evolves rapidly - APIs change between versions, constructor signatures shift, and patterns get refactored.

Prerequisites

Before writing any Mastra code, check if packages are installed:

ls node_modules/@mastra/
  • If packages exist: Use embedded docs first (most reliable)
  • If no packages: Install first or use remote docs

Documentation lookup guide

Quick Reference
User QuestionFirst CheckHow To
"Create/install Mastra project"references/create-mastra.mdSetup guide with CLI and manual steps
"How do I use Agent/Workflow/Tool?"references/embedded-docs.mdLook up in node_modules/@mastra/*/dist/docs/
"How do I use X?" (no packages)references/remote-docs.mdFetch from https://mastra.ai/llms.txt
"I'm getting an error..."references/common-errors.mdCommon errors and solutions
"Upgrade from v0.x to v1.x"references/migration-guide.mdVersion upgrade workflows
Priority order for writing code

⚠️ Never write code without checking current docs first.

  1. Embedded docs first (if packages installed)

    Look up current docs in node_modules for a package. Example of looking up "Agent" docs in @mastra/core:

    grep -r "Agent" node_modules/@mastra/core/dist/docs/references
    
  2. Source code second (if packages installed)

    If you can't find what you need in the embedded docs, look directly at the source code. This is more time consuming but can provide insights into implementation details.

    # Check what's available
    cat node_modules/@mastra/core/dist/docs/assets/SOURCE_MAP.json | grep '"Agent"'
    
    # Read the actual type definition
    cat node_modules/@mastra/core/dist/[path-from-source-map]
    
    • Why: Ultimate source of truth if docs are missing or unclear
    • Use when: Embedded docs don't cover your question
    • See: references/embedded-docs.md
  3. Remote docs third (if packages not installed)

    You can fetch the latest docs from the Mastra website:

    https://mastra.ai/llms.txt
    
    • Why: Latest published docs (may be ahead of installed version)
    • Use when: Packages not installed or exploring new features
    • See: references/remote-docs.md

Core concepts

Agents vs workflows

Agent: Autonomous, makes decisions, uses tools Use for: Open-ended tasks (support, research, analysis)

Workflow: Structured sequence of steps Use for: Defined processes (pipelines, approvals, ETL)

Key components
  • Tools: Extend agent capabilities (APIs, databases, external services)
  • Memory: Maintain context (message history, working memory, semantic recall)
  • RAG: Query external knowledge (vector stores, graph relationships)
  • Storage: Persist data (Postgres, LibSQL, MongoDB)

Critical requirements

TypeScript config

Mastra requires ES2022 modules. CommonJS will fail.

{
  "compilerOptions": {
    "target": "ES2022",
    "module": "ES2022",
    "moduleResolution": "bundler"
  }
}
Model format

Always use "provider/model-name":

  • "openai/gpt-5.2"
  • "anthropic/claude-sonnet-4-5"
  • "google/gemini-2.5-pro"

When you see errors

Type errors often mean your knowledge is outdated.

Common signs of outdated knowledge:

  • Property X does not exist on type Y
  • Cannot find module
  • Type mismatch errors
  • Constructor parameter errors

What to do:

  1. Check references/common-errors.md
  2. Verify current API in embedded docs
  3. Don't assume the error is a user mistake - it might be your outdated knowledge

Development workflow

Always verify before writing code:

  1. Check packages installed

    ls node_modules/@mastra/
    
  2. Look up current API

  3. Write code based on current docs

  4. Test in Studio

    npm run dev  # http://localhost:4111
    

Resources

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