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fa_stripHtml

Strip HTML tags and decode HTML entities out of a string, leaving the readable text behind. Use it to clean web pages or scraped content before feeding it to an agent or an index. Returns the plain text. ($0.005 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": {
      "text": "<text>"
    },
    "name": "fa_stripHtml"
  }
}

Input Schema

NameRequiredDescriptionDefault
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

A4/5.0
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 it does disclose the two things an agent most needs: the output ('Returns the plain text') and the cost ('$0.005 per call, USDC on Base'). It is implicitly a pure, non-destructive transformation. It omits the 100,000-character input cap and any failure behavior, which would be nice for a paid call.

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?

Four short sentences, front-loaded with what the tool does, then when to use it, then the return value and price. Every sentence carries information; nothing is restated from the name or title.

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

Completeness4/5

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

For a simple two-parameter pure transformation with no output schema and no annotations, the description covers purpose, use case, return value, and cost. The remaining gaps (character limit, the options object, Persian-language scope) are covered or partially covered by the schema, so the definition is adequate to call 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 description coverage is 100%, so the baseline is 3. The description adds no meaning beyond the schema for either 'text' or the loosely-specified 'options' object (schema only says 'optional, e.g. {"digits":"ascii"}'), which is the one place extra prose would have helped.

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?

States a specific verb+resource ('Strip HTML tags and decode HTML entities out of a string') and the resulting output ('readable text'), so the agent knows exactly what transformation occurs. The sibling set is all Persian-language utilities, so no disambiguation is needed, but the description never notes the fa_ Persian-context positioning that the schema's 'Persian (Farsi) text' parameter hints at.

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?

Gives a concrete usage context: 'clean web pages or scraped content before feeding it to an agent or an index.' That tells the agent when the tool fits. It stops short of naming alternatives or exclusions (e.g. use fa_normalize for plain Persian text), so it is clear context without routing guidance.

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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