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ScriptGrain

Build a voice from a website

mimic_brand

Build a voice profile from a PUBLIC brand website: discovers and scrapes up to 8 content pages, runs the stylometric analysis, and saves a ready-to-use profile (confidence capped at 0.85; the scraped excerpts are stored as the profile's samples so drafts get exemplar anchoring). Costs one brand-mimic credit from the plan's monthly allowance and takes 1-2 minutes. REQUIRES CONSENT: ask the user to explicitly accept the inspired-by terms (using a mimicked voice is their responsibility) before calling with consent=true. Rate limit: 3 per hour. Calls the ScriptGrain API, POST /v1/mimic. API reference: https://scriptgrain.com/docs/api.md

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe brand's website (e.g. monzo.com or a /blog URL).
consentYesMust be true, and only after the user explicitly agreed to the inspired-by terms.

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?

Annotations only mark this as non-read-only, non-destructive, non-idempotent, and open-world; the description goes far beyond that by disclosing credit consumption, expected duration, a rate limit of 3/hour, the consent gate, the 0.85 confidence cap, that scraped excerpts are persisted as profile samples, and the underlying POST /v1/mimic call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then layered with operational facts. It is a dense paragraph with no filler sentences, though the API endpoint and docs URL are marginally redundant for an agent choosing a tool.

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?

With no output schema, the description covers what the agent needs: what gets produced (a ready-to-use profile with anchored samples), how long it takes, what it costs, and the consent prerequisite. Nothing material about invocation is missing.

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%, so both parameters are already documented. The description still adds meaning the schema lacks: the site must be PUBLIC and it will scrape up to 8 pages from the given URL, and it spells out the consent workflow (obtain explicit user acceptance, then pass consent=true).

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 and resource ('Build a voice profile from a PUBLIC brand website') and details the mechanism (scrapes up to 8 pages, runs stylometric analysis, saves a profile). This clearly separates it from siblings like create_profile or compare_voice, which would not start from a live website.

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?

Gives concrete context for use: a public site URL, a 1-2 minute runtime, a 3/hour rate limit, a credit cost, and a hard precondition (user must accept the inspired-by terms before consent=true). It does not, however, name an alternative tool for building a voice from non-website sources (e.g. create_profile), so routing between siblings is left to inference.

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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