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aktsmm

skill-ninja-mcp-server

skillNinja_localize

Translate and localize skill descriptions between English and Japanese for AI agent skills in the skill-ninja-mcp-server.

Instructions

Translate/localize skill descriptions in the index. Provide skillName and description_en and/or description_ja. / スキル説明を翻訳・ローカライズ

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skillNameYesName of the skill to localize
description_enNoEnglish description for the skill
description_jaNoJapanese description for the skill (日本語の説明)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool translates/localizes descriptions but doesn't specify whether this creates new entries, updates existing ones, requires authentication, has rate limits, or what happens if only one language description is provided. For a mutation tool (implied by 'translate/localize'), this is a significant gap in transparency.

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 appropriately sized with two sentences (one in English, one in Japanese) that directly state the purpose and parameters. It's front-loaded with the main action and avoids unnecessary details. However, the Japanese translation adds redundancy without new information, slightly reducing efficiency.

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 (a mutation operation with 3 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral traits like whether it updates or creates entries. For a tool that modifies data, more context is needed to ensure proper usage.

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?

The schema description coverage is 100%, so the schema already documents all three parameters (skillName, description_en, description_ja) with clear descriptions. The description mentions 'Provide skillName and description_en and/or description_ja', which adds minimal context about optional parameters but doesn't provide additional meaning beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's purpose: 'Translate/localize skill descriptions in the index' with specific verbs and resources. It distinguishes from siblings like 'skillNinja_list' or 'skillNinja_search' by focusing on translation/localization rather than listing or searching. However, it doesn't explicitly differentiate from 'skillNinja_updateIndex' which might also involve updates to skill 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing skill in the index), exclusions, or compare it to sibling tools like 'skillNinja_updateIndex' which might handle similar updates. Usage is implied through the action described but lacks explicit context.

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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