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aiapplyd

AI Applyd

Translate Resume

aiapplyd_translate_resume

Translate your saved resume into a target language for international job applications. Creates a separate translated resume for that market while preserving the original.

Instructions

Translate the resume saved on the user's AI Applyd account into another language, ready to send to employers in that market. Saves the translation as a new resume and leaves the original unchanged. Requires a connected AI Applyd account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_languageYesTarget language (e.g. "Spanish", "French", "German", "Japanese")

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.3.0

TDQS

A4/5.0
Behavior4/5

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

The description goes beyond the annotations by explicitly explaining that the tool creates a new resume, leaves the original unchanged, and requires a connected AI Applyd account. It does not cover every failure mode or output detail, but it transparently describes the main side effects and prerequisite.

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?

The description is three concise sentences with the action and outcome up front. It includes necessary side-effect and prerequisite information without any filler or redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no output schema, the description covers the prerequisite, the side effect, and the intended use context. It leaves only minor ambiguity about which resume is used if the user has multiple resumes on their account, but it is otherwise complete enough for invocation.

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 only parameter, target_language, is fully covered by the schema with an example and length constraints. The description does not add any additional parameter-specific constraints or clarification beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 the verb (translate), the resource (the resume saved on the user's AI Applyd account), and the outcome (saves a translation as a new resume while leaving the original unchanged). This clearly differentiates it from sibling tools like score, optimize, cover letter generation, and auto apply.

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 communicates when the tool is useful by mentioning it is for sending resumes to employers in another language, but it does not explicitly name alternative tools or state when not to use this tool. The usage is strongly implied by the translation focus, but not explicitly contrasted with siblings.

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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