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by jneless

tos_create_bucket

Create a storage bucket in Volcengine TOS with specified name and access control permissions for object storage management.

Instructions

创建 TOS 存储桶

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aclNo访问控制权限private
bucket_nameYes存储桶名称

Implementation Reference

  • The handler function for tos_create_bucket that extracts bucket_name and acl from arguments and calls tos_client.create_bucket with appropriate ACL.
    async def create_bucket(args: Dict[str, Any]) -> List[TextContent]:
        """创建存储桶"""
        bucket_name = args["bucket_name"]
        acl = args.get("acl", "private")
        
        try:
            tos_client.create_bucket(bucket_name, tos.ACLType.ACL_Private if acl == "private" 
                                           else tos.ACLType.ACL_Public_Read if acl == "public-read"
                                           else tos.ACLType.ACL_Public_Read_Write)
            return [TextContent(type="text", text=f"成功创建存储桶: {bucket_name}")]
        except Exception as e:
            return [TextContent(type="text", text=f"创建存储桶失败: {str(e)}")]
  • Input schema definition for the tos_create_bucket tool, specifying properties for bucket_name (required) and acl (optional with enum).
    inputSchema={
        "type": "object",
        "properties": {
            "bucket_name": {
                "type": "string",
                "description": "存储桶名称"
            },
            "acl": {
                "type": "string",
                "description": "访问控制权限",
                "enum": ["private", "public-read", "public-read-write"],
                "default": "private"
            }
        },
        "required": ["bucket_name"]
    }
  • Tool registration in list_tools() function, defining the tos_create_bucket tool's name, description, and schema.
    Tool(
        name="tos_create_bucket",
        description="创建 TOS 存储桶",
        inputSchema={
            "type": "object",
            "properties": {
                "bucket_name": {
                    "type": "string",
                    "description": "存储桶名称"
                },
                "acl": {
                    "type": "string",
                    "description": "访问控制权限",
                    "enum": ["private", "public-read", "public-read-write"],
                    "default": "private"
                }
            },
            "required": ["bucket_name"]
        }
    ),
  • Dispatch logic in call_tool() that routes tos_create_bucket calls to the create_bucket handler.
    if name == "tos_create_bucket":
        return await create_bucket(arguments)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('create') but doesn't cover critical aspects like permissions required, whether creation is idempotent, error conditions (e.g., duplicate bucket names), or what happens on success (e.g., returns a bucket ID or confirmation). This is a significant gap for a mutation 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, efficient sentence ('创建 TOS 存储桶') that directly states the tool's purpose with zero waste. It's appropriately sized and front-loaded, making it easy 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?

Given the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'TOS' refers to, the result of the operation (e.g., success response or error handling), or behavioral traits like rate limits. For a tool that modifies state, this leaves critical gaps for an AI agent.

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%, with clear descriptions for both parameters (e.g., 'bucket_name' as bucket name, 'acl' as access control permission with enum values). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high coverage without extra value.

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

Purpose3/5

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

The description '创建 TOS 存储桶' (Create TOS bucket) states the basic action and resource, making the purpose understandable. However, it doesn't differentiate from sibling tools like 'tos_list_buckets' or 'tos_delete_bucket' beyond the verb, and the term 'TOS' might be ambiguous without context. It's clear but generic.

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 doesn't mention prerequisites (e.g., needing a unique bucket name), exclusions, or comparisons to siblings like 'tos_list_buckets' for viewing existing buckets. Usage is implied by the verb 'create' but lacks explicit context.

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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