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ocbenji

@bitcoinbenji/mcp

ai_translate

Translate text into any of 100+ languages. Provide target language code or name; source language is optional. Pay per call via Lightning.

Instructions

Translate between 100+ languages. [20 sats per call]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
targetYestarget language code or name
sourceNosource language (optional, auto-detect)
preimageNo(L402 mode) Preimage from paid Lightning invoice — only needed if no API key is set
macaroonNo(L402 mode) Macaroon from the previous 402 challenge
Behavior3/5

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

The description adds one behavioral trait: the cost of 20 sats per call. However, it lacks disclosure about the L402 payment flow (preimage/macaroon parameters), no confirmation of whether translation is synchronous or what happens on failure, and no annotation support. The cost note is useful but incomplete.

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 a single sentence plus a cost note, which is front-loaded and avoids unnecessary verbosity. However, given the complexity of the input schema (5 parameters, including L402 fields), a slightly more detailed explanation could be justified without becoming verbose.

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?

The description is insufficient for the tool's complexity (5 parameters, no output schema, no annotations). It does not explain the L402 payment mechanism, the difference between optional and required parameters, or the expected output format. This leaves significant gaps for an agent to use the tool correctly.

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?

Schema coverage is 80% (4 of 5 parameters have descriptions). The tool description does not add any further meaning beyond what the schema already provides for those parameters. The undocumented 'text' parameter is not clarified. Baseline 3 is appropriate as the schema carries most of the burden.

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 action ('Translate') and the scope ('between 100+ languages'), making it distinct from sibling tools like ai_grammar or ai_rewrite which focus on grammar or rewriting rather than general translation.

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 does not mention when to choose translation over other language tools, nor does it specify conditions like language support or cost implications.

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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