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farsi-tools (paid)

fa_transliterate

Transliterate Persian/Arabic script to Latin, optional URL slug ($0.01 per call, USDC on Base)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNo
textYesPersian (Farsi) text or value to process. Max 100000 characters.
optionsNooptional, e.g. {"digits":"ascii"}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose a genuine behavioral trait: the cost model ($0.01 per call, USDC on Base). However, it does not explain how payment is actually settled (wallet, API key, auto-charge), nor return format or failure behavior, leaving key invocation details unstated.

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?

A single front-loaded sentence with no filler; the core operation leads and the pricing/option qualifiers follow. Nothing redundant.

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

Completeness3/5

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

For a 3-parameter tool with no output schema and no annotations, the description omits what the transliteration returns (plain string? slug alongside text?), what 'slug' actually changes in the response, and the mechanics of the paid call. Adequate for the core operation but not complete for confident 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?

Schema coverage is 67%: 'text' is well documented (including the 100k limit) and 'options' has an example, but 'slug' is a bare boolean in the schema. The description recovers some ground by labeling slug as an 'optional URL slug', adding semantic meaning the schema lacks. Baseline 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?

States a specific verb ('Transliterate') and both the source script (Persian/Arabic) and target (Latin), which unambiguously separates it from siblings like fa_normalize, fa_fixRtl, and fa_digits. An agent can identify what this does without opening the schema.

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?

No guidance on when to use this versus fa_normalize or fa_fixRtl, no stated preconditions, no exclusions. The only contextual hint is the slug option and price, neither of which tells the agent when this tool is the right choice.

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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