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s3_create_account

Create an S3 account by binding a plan and initial bucket; requires authentication and confirm=true to run.

Instructions

Create an S3 account: bind a plan and initial bucket (s3/create_account). Requires authentication.

Input Schema

NameRequiredDescriptionDefault
bucketNoInitial bucket name
confirmYesMust be true to run the operation.
plan_idNoPlan ID from s3_list_plans
locationNoLocation from s3_get_locations

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.3
    • changedInput schema / properties / bucket / description
      Previous value: -"Имя начального бакета"New value: +"Initial bucket name"
    • changedInput schema / properties / location / description
      Previous value: -"Локация из s3_get_locations"New value: +"Location from s3_get_locations"
    • changedInput schema / properties / plan_id / description
      Previous value: -"ID тарифного плана из s3_list_plans"New value: +"Plan ID from s3_list_plans"
  2. First observedv1.0.1

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds a useful authentication requirement and names the underlying endpoint (s3/create_account), but says nothing about what binding a plan actually changes or whether the operation is reversible.

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?

Two short clauses, with the core purpose front-loaded before the endpoint and auth note. No wasted sentences, though the parenthetical endpoint reference is low-value for an agent.

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?

For a mutation tool with no output schema, the description does not indicate what a successful account creation returns (credentials, IDs, status) or how to verify completion. It is adequate given the strong annotation and schema coverage, but leaves a gap around outcome handling.

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 plan_id, location, bucket, and confirm are all documented in the schema. The description merely echoes the plan/bucket concepts and adds no format or constraint detail beyond what the schema already provides, so baseline 3 applies.

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?

States a specific verb and resource ("Create an S3 account") and clarifies the effect (binding a plan and initial bucket), which cleanly distinguishes it from s3_create_bucket and s3_create_order. However it never names those siblings explicitly, so the differentiation relies on the agent's inference.

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 supplies a prerequisite ("Requires authentication") and contextualizes the operation as an account-provisioning step, which implies when it applies. It gives no when-not guidance and does not point to alternatives such as s3_create_bucket for subsequent buckets.

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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