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beget-s3-mcp-ai-cli

s3_prefix_usage

Compute S3 storage usage grouped by first-level prefix to identify where space is consumed; paginate aggregate rows via offset for large buckets.

Instructions

Bounded usage by first-level prefixes; paginate aggregate rows with next_result_offset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bucketYes
prefixNo
max_scanNo
result_offsetNo
continuation_tokenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.2/5.0
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 disclosure burden, and it delivers very little. "Bounded" implies scan limits via max_scan and "paginate" implies a paged result set, but the description never states what the bound is, what permissions are needed, whether the operation is a read or a scan with cost implications, or what the aggregate rows contain.

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?

One short sentence, front-loaded with the scoping idea and followed by the pagination note; there is no filler. It is appropriately brief, though brevity here borders on under-specification rather than discipline.

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 five-parameter tool with zero schema descriptions, no annotations, and no output schema, the description leaves critical gaps: it never explains what "usage" is, how the aggregate is computed, why the scan is bounded, or how pagination terminates. An agent cannot confidently invoke this from the definition alone.

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% across five parameters (bucket, prefix, max_scan, result_offset, continuation_token), so the description is required to compensate and does not. Worse, it directs the agent to paginate with "next_result_offset," a name that does not exist in the schema, where the pagination fields are result_offset and continuation_token — a misleading reference.

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

Purpose2/5

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

The phrase "usage by first-level prefixes" largely restates the tool name, s3_prefix_usage, without defining what "usage" actually measures (storage bytes, object counts, request volume). It does hint at aggregation grouped by top-level prefixes, but there is no clear verb and no differentiation from siblings such as s3_largest_objects that also report size-oriented data.

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?

There is no guidance on when to choose this tool over the other thirteen s3_* siblings, nor any stated preconditions or exclusions. The only procedural hint is that aggregate rows are paginated, which is mechanics rather than routing context.

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