developing-genkit-dart▌
firebase/agent-skills · updated Apr 8, 2026
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Unified AI SDK for Dart enabling code generation, structured outputs, tools, flows, and agents.
- ›Provides core APIs for generation, tool definition, flow orchestration, embeddings, and streaming with a single interface
- ›Includes 8+ plugins for LLM providers (Google Gemini, Anthropic Claude, OpenAI GPT), Firebase AI, Model Context Protocol, Chrome browser integration, and HTTP server hosting via Shelf
- ›Built-in CLI with local development UI for flow execution, tracing, model experimentat
Genkit Dart
Genkit Dart is an AI SDK for Dart that provides a unified interface for code generation, structured outputs, tools, flows, and AI agents.
Core Features and Usage
If you need help with initializing Genkit (Genkit()), Generation (ai.generate), Tooling (ai.defineTool), Flows (ai.defineFlow), Embeddings (ai.embedMany), streaming, or calling remote flow endpoints, please load the core framework reference:
references/genkit.md
Genkit CLI (recommended)
The Genkit CLI provides a local development UI for running Flow, tracing executions, playing with models, and evaluating outputs.
check if the user has it installed: genkit --version
Installation:
curl -sL cli.genkit.dev | bash # Native CLI
# OR
npm install -g genkit-cli # Via npm
Usage:
Wrap your run command with genkit start to attach the Genkit developer UI and tracing:
genkit start -- dart run main.dart
Plugin Ecosystem
Genkit relies on a large suite of plugins to perform generative AI actions, interface with external LLMs, or host web servers.
When asked to use any given plugin, always verify usage by referring to its corresponding reference below. You should load the reference when you need to know the specific initialization arguments, tools, models, and usage patterns for the plugin:
| Plugin Name | Reference Link | Description |
|---|---|---|
genkit_google_genai |
references/genkit_google_genai.md | Load for Google Gemini plugin interface usage. |
genkit_anthropic |
references/genkit_anthropic.md | Load for Anthropic plugin interface for Claude models. |
genkit_openai |
references/genkit_openai.md | Load for OpenAI plugin interface for GPT models, Groq, and custom compatible endpoints. |
genkit_middleware |
references/genkit_middleware.md | Load for Tooling for specific agentic behavior: filesystem, skills, and toolApproval interrupts. |
genkit_mcp |
references/genkit_mcp.md | Load for Model Context Protocol integration (Server, Host, and Client capabilities). |
genkit_chrome |
references/genkit_chrome.md | Load for Running Gemini Nano locally inside the Chrome browser using the Prompt API. |
genkit_shelf |
references/genkit_shelf.md | Load for Integrating Genkit Flow actions over HTTP using Dart Shelf. |
genkit_firebase_ai |
references/genkit_firebase_ai.md | Load for Firebase AI plugin interface (Gemini API via Vertex AI). |
External Dependencies
Whenever you define schemas mapping inside of Tools, Flows, and Prompts, you must use the schemantic library.
To learn how to use schemantic, ensure you read references/schemantic.md for how to implement type safe generated Dart code. This is particularly relevant when you encounter symbols like @Schema(), SchemanticType, or classes with the $ prefix. Genkit Dart uses schemantic for all of its data models so it's a CRITICAL skill to understand for using Genkit Dart.
Best Practices
- Always check that code cleanly compiles using
dart analyzebefore generating the final response. - Always use the Genkit CLI for local development and debugging.
How to use developing-genkit-dart on Cursor
AI-first code editor with Composer
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 developing-genkit-dart
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches developing-genkit-dart from GitHub repository firebase/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate developing-genkit-dart. Access the skill through slash commands (e.g., /developing-genkit-dart) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★63 reviews- ★★★★★Amina Torres· Dec 28, 2024
developing-genkit-dart fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Amelia Verma· Dec 24, 2024
Keeps context tight: developing-genkit-dart is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Isabella Singh· Dec 20, 2024
Useful defaults in developing-genkit-dart — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Pratham Ware· Dec 16, 2024
Registry listing for developing-genkit-dart matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Naina Yang· Dec 16, 2024
Solid pick for teams standardizing on skills: developing-genkit-dart is focused, and the summary matches what you get after install.
- ★★★★★Sofia Anderson· Dec 12, 2024
We added developing-genkit-dart from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Amina Flores· Dec 4, 2024
Registry listing for developing-genkit-dart matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Advait Thomas· Nov 23, 2024
Useful defaults in developing-genkit-dart — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Anaya Malhotra· Nov 19, 2024
We added developing-genkit-dart from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Hassan Li· Nov 15, 2024
developing-genkit-dart is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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