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peter14l

flutter-orchestrator

by peter14l

scaffold_flutter_ai_module

Scaffold Flutter AI modules with Gemini SDK, providing streaming responses, Riverpod state controllers, and interactive chat views for integration.

Instructions

Scaffolds Google Generative AI (Gemini) SDK integration for Flutter with streaming responses, Riverpod state controllers, and interactive chat views.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNogoogle-generative-ai
featureNameYesName of the AI feature (e.g. 'ChatAssistant', 'SmartScanner', 'Copilot').
systemInstructionNoCustom system instruction/persona for the AI model.
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions scaffolding but doesn't disclose side effects (e.g., file creation, dependency changes, whether it modifies existing code), required permissions, or reversibility. For a scaffolding tool that likely creates files, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with the core purpose. Efficient and no wasted words, though it could benefit from a second sentence on usage context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a scaffolding tool with 3 parameters and no output schema, the description is thin. It doesn't explain what files are generated, how the provider parameter affects output, or what the agent should expect after invocation. Siblings like scaffold_flutter_backend likely have similar gaps, but this tool's complexity warrants more detail.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67% (featureName and systemInstruction have descriptions, provider has enum but no description). The description adds context about what the scaffold includes but doesn't elaborate on parameter usage beyond schema. The provider enum is self-explanatory, but systemInstruction could use more context on how it's used.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scaffolds Gemini SDK integration for Flutter, listing specific components (streaming responses, Riverpod state controllers, interactive chat views). It distinguishes from siblings like scaffold_flutter_backend or scaffold_flutter_database, though it doesn't explicitly name a sibling it is not.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for Flutter AI features but doesn't explicitly state when to use this vs alternatives like generate_flutter_api_bridge or scaffold_flutter_offline_resilience. No exclusions or alternative routing provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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