list_buckets
Retrieve a list of all S3 buckets in your AWS account to manage storage resources and organize data.
Instructions
List all S3 buckets in your AWS account.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve a list of all S3 buckets in your AWS account to manage storage resources and organize data.
List all S3 buckets in your AWS account.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it's a listing operation but doesn't mention whether it requires specific AWS permissions, how results are returned (pagination, format), rate limits, or error conditions. This leaves significant gaps for an agent to understand operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple listing operation and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and multiple sibling tools, the description is insufficiently complete. It doesn't explain what format the bucket list returns, how to handle large numbers of buckets, or how this differs from other listing operations. The agent would need additional context to use this effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the input requirements. The description appropriately doesn't waste space discussing non-existent parameters, earning a baseline score of 4 for this zero-parameter case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all S3 buckets in your AWS account'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_objects' or 'bucket_info', which would require more specific scope clarification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_objects' or 'bucket_info'. It mentions no prerequisites, exclusions, or contextual factors that would help an agent choose between similar listing operations.
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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