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ro_create_char

Create a Ragnarok Online character in a designated slot by providing name, job, sex, hair style, and hair color, after verifying the client is requesting character properties.

Instructions

Create a character in the given slot. Only valid while OpenKore is asking for character properties — call ro_prompt first to confirm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobNonovice
sexNoM
nameYesCharacter name; the server enforces a 4 char minimum.
slotNo
hairColorNo
hairStyleNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses the state dependency (that it only works during a specific prompt), which is a critical behavioral trait. It does not, however, describe side effects, error behavior, or what happens if the precondition is violated. For a mutation tool (creating a character), this is a moderate gap, but the core limitation is stated.

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?

Two clauses in a single sentence, with the purpose front-loaded and the usage constraint appended. No unnecessary words, every part earns its place. It is minimally verbose while conveying the essential information.

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 tool's complexity (6 parameters, no output schema, no annotations), the description is sparse. It doesn't mention what happens after successful creation, any return values, error conditions, or how to handle slot conflicts. The prerequisite hint about ro_prompt is useful but is the only piece of operational context. An agent would need to infer most behavior from the name and schema alone, which is inadequate for a state-dependent creation action.

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 only 17% (only 'name' has a description in the schema). The tool description adds no explanation of any parameter, failing to compensate for the low coverage. It doesn't clarify what 'slot' means in context, what job/sex options imply, or the significance of hairColor/hairStyle. The agent must infer meaning from enums and names, which is insufficient for a 6-parameter tool.

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?

The description states the action clearly ('Create a character') and specifies the target resource (the given slot). It does not differentiate from the sibling ro_select_char, which also deals with characters, but the verb 'create' implies a distinct operation. Since it doesn't explicitly contrast with any sibling, it loses the point for clear sibling differentiation.

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 gives an explicit condition for valid usage: only while OpenKore is asking for character properties, and it instructs to call ro_prompt first to confirm. This provides a clear when-to-use rule and even names a prerequisite tool. However, it doesn't mention when not to use it or alternatives, but the condition is strong enough to guide an agent.

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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