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Ni Biashara Shelves — Africa FX, freight & compliance checks (x402)

English ↔ Swahili localization — instant machine pass, up to 120 words

localize_text
Read-only

English ↔ Swahili localization — instant machine pass, up to 120 words. Machine localization (open translation model, run in-process), returned in the paid response with no ticket or wait. Suited to UI strings, alt text and short product copy. Machine-grade output, labeled as such. Human-reviewed copy up to 500 words is a separate shelf, swahili-localization-500w. $0.25 USDC on Base. Returns the x402 URL to GET (402 → PAYMENT-SIGNATURE → delivery). Free to call this tool; payment happens on the URL.

Input Schema

NameRequiredDescriptionDefault
textYesthe text to localize, up to 120 words (required)
directionNoen-sw or sw-en (optional, default en-sw)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover safety (readOnlyHint, destructiveHint=false, openWorldHint), and the description adds substantial context beyond them: the model runs in-process, output is machine-grade and labeled as such, cost is $0.25 USDC on Base, and the delivery is an x402 URL flow (402 → PAYMENT-SIGNATURE → delivery). This discloses pricing, quality tier, and settlement mechanics that annotations cannot carry.

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?

Front-loaded with the core purpose and scope, then layered detail on quality, price, and payment. It repeats the title verbatim as its opening sentence and slightly restates the "machine" nature, which is mild redundancy, but every section is relevant and well-ordered.

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

Completeness5/5

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

With no output schema, the description carries the return burden and does so: it explains the paid response, the x402 URL to GET, and the 402/payment-signature handshake. Combined with the tier guidance and pricing, an agent has everything needed to invoke and interpret the result.

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 100%, so both params (text, direction) are already fully documented with the 120-word limit and en-sw/sw-en default. The description restates the word limit but adds no new syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb (localize) and resource (English↔Swahili text) with a clear scope limit (up to 120 words), and explicitly distinguishes itself from the human-reviewed sibling swahili-localization-500w. An agent can tell this apart from the other shelf tools without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit fit guidance ("Suited to UI strings, alt text and short product copy") and names the alternative shelf (swahili-localization-500w) with its condition (human-reviewed, up to 500 words). It also clarifies the payment model — "Free to call this tool; payment happens on the URL" — removing the biggest source of agent confusion.

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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