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QuassLabs API

by com.quasslabs
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humanize_text

Read-onlyIdempotent

Rewrite text to remove AI-writing tells. POST prose and get it back with the mechanical tells fixed (AI vocabulary swapped for plain words, filler phrases stripped, em-dash overuse reduced, significance inflation deflated) plus a change log, before/after ai-ness scores, and a residual list of tells that need human judgment (not auto-rewritten). Code fences, inline code, URLs, and quotes are never touched. Deterministic, no LLM. Sister to humanizer_score (the detector).

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": "humanize_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe prose to rewrite (up to 100k chars).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnly/idempotent/non-destructive, and the description adds substantial context beyond that: it is deterministic with no LLM, code fences, inline code, URLs and quotes are never touched, and it returns a change log, before/after ai-ness scores, and a residual list requiring human judgment. That preservation and return-shape detail is exactly what an agent needs before calling.

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?

The purpose is front-loaded in the first sentence, followed by output and preservation guarantees in a tight sequence. Despite being information-dense, every clause carries actionable content and nothing is filler.

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?

For a single-parameter tool with no output schema, the description covers input expectations, transformation behavior, invariants, and the full shape of the response. There is no material gap an agent would need to infer.

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 coverage is 100% and the single text parameter is documented, so the baseline is 3. The description adds meaning beyond the schema by clarifying that only prose is rewritten while code fences, inline code, URLs and quotes are preserved, which tells the agent what portion of the input actually matters.

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 (rewrite) and resource (text to remove AI-writing tells) and enumerates the exact transformations. It also names the sibling humanizer_score as the detector counterpart, so an agent can pick between the two without opening either schema.

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?

"POST prose and get it back" gives clear usage context, and naming humanizer_score as the detector implicitly routes detection-only needs to that sibling. It stops short of explicit when-not-to-use guidance (e.g. non-prose input, or when only scoring is wanted), so it falls just short of a 5.

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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