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greet

Generate personalized greeting messages in friendly, formal, or enthusiastic styles to initiate communication through the Strands MCP Server.

Instructions

Greet someone with different styles.

Returns: str: A greeting message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the person to greet
styleNoGreeting style - "friendly", "formal", or "enthusiastic"friendly

Implementation Reference

  • The 'greet' tool handler: decorated with @tool from strands, implements greeting logic using a dictionary of styles based on input parameters 'name' and 'style'. The docstring provides input schema details.
    @tool
    def greet(name: str, style: str = "friendly") -> str:
        """Greet someone with different styles.
    
        Args:
            name: The name of the person to greet
            style: Greeting style - "friendly", "formal", or "enthusiastic"
    
        Returns:
            str: A greeting message
        """
        styles = {
            "friendly": f"Hey {name}! Great to see you! 👋",
            "formal": f"Good day, {name}. It is a pleasure to meet you.",
            "enthusiastic": f"🎉 {name}!!! SO excited to see you! 🚀✨",
        }
    
        return styles.get(style, styles["friendly"])
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a greeting message but doesn't cover aspects like side effects, error handling, or performance. For a tool with no annotations, this leaves significant behavioral gaps.

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?

The description is brief and front-loaded with the core purpose. The second sentence about return values is somewhat redundant since no output schema exists, but it doesn't waste space. Overall, it's efficient with minimal fluff.

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

Completeness3/5

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

Given the tool's low complexity (simple greeting function), 100% schema coverage, and no output schema, the description is adequate but incomplete. It covers the basic purpose and return type but lacks behavioral context and usage guidelines, which are needed for full understanding.

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 description coverage is 100%, so the schema fully documents both parameters ('name' and 'style' with default and enum-like values). The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline for high schema coverage.

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's purpose: 'Greet someone with different styles.' It specifies the verb ('greet') and resource ('someone'), though it doesn't explicitly distinguish from sibling tools like 'invoke_agent' or 'mcp_client'. The purpose is clear but lacks sibling differentiation.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description mentions 'different styles' but doesn't specify contexts, prerequisites, or exclusions. Without usage guidelines, the agent must infer appropriate scenarios.

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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