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CounselorAI

by io.github.The-825
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Humanize reader-facing text

humanize
Read-only

Rewrite reader-facing prose so it sounds direct, specific, and personal without changing facts or inventing a voice. Use it for outreach, emails, letters, posts, and narrative copy. It preserves quoted text and checks the result against the source. It does not evade or promise to beat AI detectors. Do not use it for code, SQL, JSON, legal text, or technical specifications.

Cost: about 413 credits (~$0.413) per call.

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"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe reader-facing prose to edit.
audienceNoWho will read the text. This changes vocabulary and formality, not the facts.general
strengthNolight makes surface fixes, standard rewrites AI-sounding sentences, aggressive may rebuild paragraph flow.standard
preserveFormattingNoKeep headings, lists, paragraph breaks, links, and other formatting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses meaningful behavioral traits beyond annotations: it preserves quoted text, checks the result against the source, does not invent a voice, and does not claim to evade AI detectors. These are important non-obvious behaviors that help an agent set expectations correctly.

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 description is front-loaded with the core purpose, followed by usage guidance, behavioral constraints, and an explicit exclusion list. Every sentence adds useful information, and the cost note is clearly separated.

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?

The description covers what the tool does, when to use it, what it preserves, and what it does not promise. The absence of an output schema is not a major gap because the expected result is implied by the rewrite task, though a brief note on return format would make it fully complete.

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 input schema already documents all parameters well. The description does not add parameter-specific details beyond the schema, which aligns with the baseline of 3 for high schema coverage.

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?

The description states a specific verb ('rewrite'), a clear resource ('reader-facing prose'), and the transformation goals ('direct, specific, personal') without changing facts. It also differentiates from other tools by explicitly excluding code, SQL, JSON, legal text, and technical specs.

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

Usage Guidelines5/5

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

Provides explicit use cases ('outreach, emails, letters, posts, and narrative copy') and explicit negative guidance ('Do not use it for code, SQL, JSON, legal text, or technical specifications'). This gives the agent clear conditions for when to select this tool over others.

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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