ScorpTech x402 Tools

Text Wrap

text_wrap

Read-onlyIdempotent

Wrap text to a measure in Helvetica or Helvetica-Bold. Hard breaks are LF, CR, or CRLF. Inside a paragraph, spaces collapse to one and leading and trailing spaces are dropped. A word moves to the next line when it does not fit. A word wider than the whole measure breaks between characters, and those lines are marked broken. The width of each line uses the same AFM rounding as text-width. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/text-wrap

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>",
      "width": "<width>"
    },
    "name": "text_wrap"
  }
}

Input Schema

Name	Required	Description	Default
`font`	No		helvetica
`size`	No		12
`text`	Yes
`width`	Yes	Measure in points

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 23, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description still adds real value: the paid-call model ($0.001 USDC per successful call via x402 on Solana), the HTTPS equivalent endpoint, and deterministic edge-case behavior (over-wide words break mid-character and those lines are flagged broken). It does not mention failure/refund behavior or rate limits, keeping it below a 5.

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?

Front-loads the core action, then packs the line-breaking semantics into short declarative sentences; the pricing/endpoint sentence is dense but necessary information. No filler.

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?

The description covers input semantics and edge-case wrapping behavior, and there is no output schema, yet it never states the return shape (e.g., array of lines plus broken-line flags) even though 'marked broken' hints at it. The unexplained 'size' parameter leaves a real gap for a 4-parameter tool.

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 only 25% (only 'width' is documented), so the description must compensate. It does clarify the font enum choices (Helvetica vs Helvetica-Bold) and that width is a measure in points, but it never explains 'size' (a string defaulting to '12', presumably point size) or the 8000-character text cap. Partial compensation only.

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?

Opens with a specific verb+resource+scope: 'Wrap text to a measure in Helvetica or Helvetica-Bold.' It is clearly a typesetting/line-breaking operation, distinct from the numeric siblings, and it names text-width as its rounding reference. It does not, however, distinguish itself from near-neighbors like text_fit, text_block, or text_ellipsis.

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

Usage Guidelines3/5

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

The wrapping rules imply the use case (produce hard-broken lines at a given measure), but there is no explicit statement of when to prefer this over text_fit, text_block, or text_ellipsis, nor any prerequisite or exclusion 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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