mastra

mastra-ai/skills · updated Apr 8, 2026

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

Reference guide for building agents and workflows with current Mastra APIs.

  • Always verify against embedded docs in node_modules/@mastra/*/dist/docs/ (installed version) or remote docs at https://mastra.ai/llms.txt before writing code; training data is outdated
  • Core building blocks: Agents (autonomous, decision-making), Workflows (structured sequences), Tools (extend capabilities), Memory (maintain context), and RAG (external knowledge)
  • Requires ES2022 modules in TypeScript config and
skill.md

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Everything you know about Mastra is likely outdated or wrong.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

Available files

References

User Question First Check How To
"Create/install Mastra project" references/create-mastra.md Setup guide with CLI and manual steps
"How do I use Agent/Workflow/Tool?" references/embedded-docs.md Look up in node_modules/@mastra/*/dist/docs/
"How do I use X?" (no packages) references/remote-docs.md Fetch from https://mastra.ai/llms.txt
"I'm getting an error..." references/common-errors.md Common errors and solutions
"Upgrade from v0.x to v1.x" references/migration-guide.md Version upgrade workflows

Scripts

  • scripts/provider-registry.mjs: Look up current providers and models available in the model router. Always run this before using a model to verify provider keys and model names.

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
    • More information: 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
    • More information: 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, observational memory)
  • RAG: Query external knowledge (vector stores, graph relationships)
  • Storage: Persist data (Postgres, LibSQL, MongoDB)

Mastra Studio

Studio provides an interactive UI for building, testing, and managing agents, workflows, and tools. It helps with debugging and improving your applications iteratively.

Inside a Mastra project, run:

npm run dev

Then open http://localhost:4111 in your browser to access Mastra Studio.

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" when defining models using Mastra's model router.

Use the provider registry script to look up available providers and models:

# List all available providers
node scripts/provider-registry.mjs --list

# List all models for a specific provider (sorted newest first)
node scripts/provider-registry.mjs --provider openai
node scripts/provider-registry.mjs --provider anthropic

When the user asks to use a model or provider, always run the script first to verify the provider key and model name are valid. Do not guess model names from memory as they change frequently.

Example model strings:

  • "openai/gpt-5.4"
  • "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

how to use mastra

How to use mastra on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add mastra
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

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

The skills CLI fetches mastra from GitHub repository mastra-ai/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/mastra

Reload or restart Cursor to activate mastra. Access the skill through slash commands (e.g., /mastra) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.730 reviews
  • Nikhil Mehta· Dec 20, 2024

    mastra reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chaitanya Patil· Dec 12, 2024

    We added mastra from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Li Jain· Nov 11, 2024

    Registry listing for mastra matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yusuf Chen· Nov 7, 2024

    Useful defaults in mastra — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Nov 3, 2024

    mastra fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ren Martinez· Oct 26, 2024

    mastra has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Oct 22, 2024

    mastra is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • James Jain· Oct 2, 2024

    Keeps context tight: mastra is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • James Ghosh· Sep 9, 2024

    mastra is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ava Singh· Sep 9, 2024

    mastra fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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