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Как дела у сайта

site_status
Read-only

How a site is doing: whether it is being served and how its build ended.

`project` is an id or a slug. One call instead of three (project,
deploys, live check of the address): an agent needs the conclusion, not
the raw material to assemble it from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesПроект: слаг (`my-site`) или id. Слаг — то, что видно в адресе сайта; если пользователь назвал сайт словами, возьми слаг из `my_projects`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
projectYes
servingYes
http_codeYes
last_errorYes
next_actionYes
last_deploy_stageYes
last_deploy_statusYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / project / description
      Added value: +"Проект: слаг (`my-site`) или id. Слаг — то, что видно в адресе сайта; если пользователь назвал сайт словами, возьми слаг из `my_projects`."
  2. Added

TDQS

A4.1/5.0
Behavior3/5

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

The annotation readOnlyHint=true already establishes this as a safe read operation. The description adds useful context about combining three checks into a single conclusion, but does not disclose other behavioral details like potential delays, caching, or error scenarios. This is acceptable but not rich.

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 compact and front-loaded: it states the purpose in a single sentence, then adds the parameter clarification and rationale in a short parenthetical. Every sentence earns its place with no 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?

Given the tool's simplicity (one parameter, fully described schema, output schema present) and the read-only annotation, the description is complete enough. It adequately covers behavior and usage context without needing to explain return values or additional scenarios.

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 schema fully documents the 'project' parameter. The description briefly restates the id/slug distinction and references my_projects, but adds no new semantics beyond what the schema already provides.

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 clearly states what the tool does: it reports whether a site is being served and how its build ended. It also distinguishes itself from alternatives by positioning itself as the one-call conclusion instead of assembling raw data from three separate tools (project, deploys, live check).

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?

It explicitly describes when to use the tool: when the agent needs the conclusion rather than raw material. It also tells the user to get the slug from my_projects if needed. While it doesn't name sibling tools explicitly, it clearly enumerates the individual checks it replaces, giving sufficient context.

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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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct resource and action. The deploy lifecycle is cleanly separated into cancel, retry, rollback, diagnose, logs, list, and status, while the site_* tools each answer a different question. Even the two compose_landing tools are explicitly differentiated for model vs. internal use.

Naming Consistency3/5

Tool names mix verb-first patterns (check_domain, list_deploys, connect_analytics) with noun-first patterns (site_issues, deploy_logs, env_vars), and some are bare verbs (rollback, whoami). The naming is descriptive and readable, but not consistent enough to predict the style for a new tool.

Tool Count2/5

27 tools exceeds the typical well-scoped range and pushes into 'too many' territory. While the server covers a broad platform scope, many tools are highly specialized (check_copy, site_screenshot), and an agent may be overwhelmed by the sheer number of choices. Consolidation could reduce the load.

Completeness4/5

The core lifecycle is solid: compose, publish, monitor, diagnose, and rollback, with supporting tools for domains, analytics, performance, and content inspection. However, there are no delete/remove operations for projects, domains, or integrations, and integration management is limited to adding. These are minor gaps that agents can work around, but they are notable for a full platform.