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Add a website

create_site

Adds a website to the account and returns it with its install.script_tag. Fails with plan_limit when the plan has no free site left. To install the live chat, paste the returned script tag once before in the site's shared layout.

Input Schema

NameRequiredDescriptionDefault
urlYesThe site's address, e.g. https://example.com (also used as the first allowed domain and, without name, as the name).
nameNoA display name for the site.
colorNoThe bubble's color, #RRGGBB.
themeNoStyle of the bubble: neo (thick borders and offset shadows, the default), doux (soft, rounded, no borders), minimal (flat, thin lines) or nuit (dark). The site color applies to each.
domainsNoMore addresses where the bubble may load (e.g. example.lovable.app, localhost).
positionNoSide of the screen for the bubble.
greeting_enabledNoShow a short welcome message above the bubble, in the visitor's language.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and destructiveHint=false, so the bar is lower, yet the description adds genuinely new behavior: a documented failure mode ('plan_limit' when no free site remains) and the shape of the returned install artifact. It does not cover permissions/scope or what happens to the site's state after creation.

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 sentences, each earning its place: what it does and returns, the failure condition, and the post-call action. Purpose and return value are front-loaded with no redundant restatement of the title.

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 7-parameter mutation with no output schema, the description covers the essential return value (install.script_tag) and the key error case, and the schema handles all parameter detail. Missing only peripheral context such as whether the site is immediately active or any auth/plan prerequisites beyond the limit error.

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% and the property descriptions are unusually rich (url doubles as first allowed domain and fallback name, theme enum explained, color format given), so the schema carries parameter meaning. The description adds no parameter-level guidance of its own beyond the script tag workflow.

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 ('Adds a website to the account') and adds the return payload ('returns it with its install.script_tag'), which separates it cleanly from update_site and list_sites in the sibling set.

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?

Implies creation-time usage and gives a concrete follow-up workflow (paste the returned script tag before </body> in the shared layout), which tells the agent what to do after the call. It never explicitly contrasts with update_site for existing sites, so the when-not 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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