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shamimlaravel

laravel13-livewire4.2.1-mcp

generate_observer

Creates a Laravel model observer to handle model events like creating, updating, and deleting with custom actions.

Instructions

Generate a Laravel model observer for handling model events (creating, updating, deleting, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
eventsNo
modelClassYes
Behavior2/5

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

With no annotations provided, the description must carry the full burden of disclosing behavior. It only states what the tool does (generates an observer) but does not mention side effects such as file creation, overwriting existing files, naming conventions, or whether it requires existing models. It also doesn't clarify the output format or whether it modifies the Laravel project structure. This lack of behavioral context is a significant gap for a code generation tool.

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

Conciseness5/5

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

The description is a single, concise sentence that immediately communicates the tool's purpose. It contains no fluff, repetition, or unrelated details, making it easy for an agent to parse quickly.

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?

The tool has three parameters, no output schema, and no annotations. The description only provides a high-level purpose without elaborating on parameter semantics, expected behavior, or return values. This is insufficient for an agent to confidently invoke the tool correctly, especially given the complexity of configuring event handlers and model class references.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not explain the three parameters (model, events, modelClass). It only mentions event types ('creating, updating, deleting, etc.'), which loosely aligns with the events parameter, but it fails to clarify the distinction between 'model' and 'modelClass', the structure of the events array, or the meaning of 'action'. The description adds minimal value beyond the raw schema, leaving parameter usage ambiguous.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Generate a Laravel model observer for handling model events.' It specifies the resource (model observer) and the exact action (generate), and it differentiates from sibling tools like generate_eloquent_model (which creates models) and generate_policy (which handles authorization). The mention of specific events (creating, updating, deleting) adds concrete scope.

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 when to use it: when a Laravel model observer is needed to handle model events. However, it provides no explicit guidance on when not to use it or how it compares to alternative tools (e.g., using events directly, policies, or model boot methods). No context is given about prerequisites or scenarios where this tool is the best choice.

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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