toolvend - utility APIs for agents

text-clean

Clean text: strip HTML, normalise unicode/whitespace, dedupe lines. Returns cleaned text plus stats. Paid per call: $0.003 in USDC via x402.

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": "text-clean"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes	Input text (max 500,000 characters)
`options`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 26, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- removedInput schema / properties / options / additionalProperties
```
Removed value: -false
```
First observedAug 2, 2026

TDQS

A3.8/5.0

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 add genuinely non-obvious context: the return payload ('cleaned text plus stats') and a per-call cost of $0.003 USDC via x402. However, it omits critical behavior for the nested `options` object — notably whether omitted flags default to on or off — and says nothing about idempotency or failure modes for oversized input.

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?

Two tight sentences with zero filler: the transformation list is front-loaded, followed by return shape and cost. Every clause carries information an agent needs.

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 two-parameter utility with no output schema, the description covers the operation set, the return shape in general terms, and the unusual payment requirement — the biggest omission risk. Remaining gaps (option flag defaults, what 'stats' contains) are modest but real given there is no output schema to fall back on.

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 50%: `text` is documented in-schema with its 500,000-character limit, while the five nested boolean options have no descriptions or defaults. The description usefully names four of those flags (stripHtml, dedupeLines, normalizeUnicode, normalizeWhitespace) but never mentions `lowercase` and never states default behavior, so it only partially compensates.

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 (clean) and resource (text), then enumerates the concrete transformations: strip HTML, normalise unicode/whitespace, dedupe lines. Siblings are unrelated utilities (dns, qr, vat), so no sibling differentiation is required, and the description still makes the operation's scope unmistakable.

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 listed operations imply when the tool is useful (preparing text for downstream processing), but there is no explicit when-to-use/when-not guidance or precondition statement. An agent must infer applicability from the transformation list.

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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