Skip to main content
Glama

translate

Converts provided text into a specified target language via verified, retryable commands, enabling reliable multilingual content output.

Instructions

Translate a piece of text into a given target language. [conductor: verified stochastic command]

Input Schema

NameRequiredDescriptionDefault
textYes
target_languageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, and it discloses almost nothing: no return format (a plain translated string?), no handling of unknown or unsupported languages, no notes on whether the source language is auto-detected. The bracketed 'conductor: verified stochastic command' fragment is internal noise rather than behavioral information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is tight and front-loaded, which is good. The trailing '[conductor: verified stochastic command]' artifact adds no value to an agent and dilutes an otherwise efficient description.

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?

For a simple two-parameter tool with no annotations and no output schema, the description should at minimum clarify the target_language format and what is returned. Neither is covered, so an agent could easily invoke it with a malformed language value or misread the result.

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 0%, so both required parameters are documented only by their names. The description loosely maps to them ('piece of text', 'given target language') but never states the expected format for target_language (ISO code vs. English name) or any text-length expectation, leaving the critical ambiguity unresolved.

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 gives a specific verb ('Translate') and resource ('a piece of text') plus the output direction ('into a given target language'), which is enough to distinguish it from utility siblings like slugify or word_count. It stops short of differentiating from the adjacent detect_language tool, but the purpose itself is unambiguous.

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?

There is no guidance on when to use this versus alternatives such as detect_language, nor any prerequisites or constraints (e.g., whether text length is limited, whether target_language must be provided by name or code). The agent must infer usage entirely from the verb.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.