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hamravesh_create_database

Create a managed database (DBaaS) by specifying engine, version, plan, CPU, RAM, and disk. Supports PostgreSQL, MySQL, MongoDB, and Redis.

Instructions

ساخت یک دیتابیسِ مدیریت‌شده (DBaaS). واحدها: cpu = millicore (۱۰۰۰=۱ core)، ram/disk = MB. num_of_standbys = تعدادِ standby (۰ = فقط master). plan را از GET /dbaas/api/v1/app/plans/ بگیر (code_name مثل fixed-plan-0). engine باید دقیقاً با همان حروف باشد: PostgreSQL / MySQL / MongoDB / Redis / … . cluster_id و namespace_id را از یک دیتابیس یا اپِ موجود (list/get) بردار. (غیرفعال — برای فعال‌سازی HAMRAVESH_ALLOW_WRITE=1) [پیش‌نمایش: dry_run:true یا env HAMRAVESH_DRY_RUN=1]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
engineYesنوعِ دیتابیس، مثل PostgreSQL
versionYesنسخه، مثل 17.4
planYescode_name پلن، مثل fixed-plan-0
cpuYesmillicore (۱۰۰۰=۱ core)
ramYesMB
diskYesMB
num_of_standbysNoتعدادِ standby؛ پیش‌فرض ۰
is_managedNoپیش‌فرض true
cluster_idYes
namespace_idYes
orgNo
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool is disabled by default (requires HAMRAVESH_ALLOW_WRITE=1) and offers a dry-run preview. However, it lacks crucial behavioral details such as whether the creation is synchronous or asynchronous, required permissions, error handling, or idempotency. The description is insufficient for an agent to safely invoke the tool.

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 front-loaded with purpose and packs multiple instructions into a single paragraph. It is reasonably concise for the amount of information, though it could benefit from bullet points or better organization for readability.

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 complexity (12 parameters, no output schema), the description provides important operational context like unit guidelines and preview mode. However, it does not explain the actual API call details, error conditions, or result format, leaving gaps for an AI agent to invoke it reliably.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds significant meaning beyond the schema: it explains units for cpu, ram, disk; clarifies num_of_standbys default; directs how to obtain plan from a separate endpoint; specifies engine casing requirements; and notes that cluster_id/namespace_id come from existing resources. This compensates for the 67% schema coverage, though not all parameters are explicitly explained.

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

Purpose5/5

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

The description clearly states 'Create a managed database (DBaaS)', which is a specific verb+resource. It distinguishes from sibling tools like list_databases, get_database, and delete_database by focusing on creation. The added units and instructions further clarify the tool's purpose.

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

Usage Guidelines4/5

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

The description provides explicit guidance on prerequisites: how to obtain plan, engine format requirements, and sourcing cluster_id/namespace_id. It also mentions the disabled state and preview mode. However, it does not explicitly state when to use this tool over alternatives like list or get, nor does it list exclusions.

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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