FarsiTools (paid)

fa_similarity

Measure the similarity of two Persian strings as a trigram Jaccard score from 0 to 1. Use it to detect near-duplicate Persian text, deduplicate a corpus, or rank one Persian string against another. Returns the similarity score. ($0.01 per call, USDC on Base)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "a": "<a>",
      "b": "<b>"
    },
    "name": "fa_similarity"
  }
}

Input Schema

Name	Required	Description	Default
`a`	Yes	first string
`b`	Yes	second string

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the algorithm (trigram Jaccard), the output scale (0-1), and the cost model ($0.01 per call, USDC on Base), which is meaningful operational context an agent needs before calling. It omits edge-case behavior (empty strings, directionality/symmetry) that would fully discharge the no-annotation burden.

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?

Three short sentences, front-loaded with the metric and range, then usage, then return and cost. No sentence is filler; even the pricing parenthetical is actionable.

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?

Although there is no output schema, the description states the return value and its scale, and the two-parameter surface is fully covered. Nothing an agent needs to invoke and interpret this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3; the schema only says 'first string'/'second string', while the description adds the important domain constraint that both operands must be Persian strings. That is genuine added meaning beyond the schema, though it does not explain ordering or length limits.

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 and resource ('Measure the similarity of two Persian strings') and pins down the exact metric and output range (trigram Jaccard, 0 to 1). Among siblings that are all single-purpose fa_* utilities, an agent can immediately tell this one apart from fa_stats or fa_normalize.

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

Usage Guidelines4/5

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

Names three concrete use cases — near-duplicate detection, corpus deduplication, and ranking one string against another — which tells the agent when this tool is the right choice. It stops short of naming an alternative sibling or stating when not to use it, so it lacks explicit exclusions.

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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