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Brand-voice rewrite

parserail_rewrite

Rewrite any copy to match your brand voice. Describe the desired voice or paste a sample to get the revised text and a list of changes.

Instructions

Any copy → your brand voice. Describe the voice or paste a sample; get the rewrite and what changed. Costs credits from the account wallet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoe.g. "tighter, more confident".
textYes
voiceNoDescribe the voice or paste a sample of it.
lengthNo
audienceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.5

TDQS

A3.7/5.0
Behavior4/5

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

The description adds real behavioral context beyond annotations: 'Costs credits from the account wallet' discloses a monetary side effect, and 'get the rewrite and what changed' discloses the response shape, which matters since no output schema exists. This is consistent with readOnlyHint:false and idempotentHint:false. No contradiction.

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?

Three tight sentences, front-loaded with purpose, using compact arrow notation. Every sentence earns its place: the transformation, the input mechanism, and the cost side effect. No filler or redundant schema restatement.

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 moderate-complexity generation tool with no output schema, the description covers the essential call contract: what goes in, how to specify voice, what comes back, and the cost implication. It falls short only on the undocumented goal/length/audience parameters, which the sparse schema leaves unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 40%, so the description must compensate for the undocumented text, length, and audience parameters, but it does not. It only restates the voice parameter ('describe the voice or paste a sample'), which the schema already documents, adding no new meaning for goal, length, audience, or text.

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-resource pair ('Any copy → your brand voice') with an explicit input-output contract: copy in, brand-voice rewrite plus change log out. It clearly distinguishes itself from the sibling family, which is dominated by analysis tools (parse, extract, summarize, classify), by being a generation/transformation tool.

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

Usage Guidelines2/5

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

The description says 'Any copy' but gives no when-to-use vs when-not-to-use guidance. It never names alternatives like parserail_reply, parserail_outreach, or parserail_product_copy, which are also generation tools an agent could confuse it with. There is no exclusion criteria or routing hint beyond the cost warning.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.