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accsly.io VPS and accounts price comparison

Search account offers

search_accounts
Read-onlyIdempotent

Search the catalog of ready-made accounts (Telegram, TikTok, Gmail, Steam, ChatGPT and 70+ platforms) compared across independent shops. Returns matching platforms with their categories (slugs and URLs) and the most bought in-stock offers with price, stock, shop, product page and buy link (list_offers sorts one platform or category by price).

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYesPlatform or product words, e.g. "telegram", "gmail aged", "tiktok ads".
localeNoLanguage of names and page links; also the price currency: ru = RUB, en = USD, de/es/pt = EUR, tr = TRY.en
categoryNoCategory slug within the platform.
platformNoPlatform slug to search within (from earlier results), e.g. "telegram".
max_priceNoMaximum price per item in the locale currency.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered; the description adds real value by disclosing the return shape (platform categories with slugs/URLs, plus most-bought in-stock offers with price, stock, shop, product page and buy link). It does not discuss pagination or result ranking beyond 'most bought in-stock', which keeps it short of a 5.

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?

Two sentences, front-loaded with what the tool searches, then the return payload. The second sentence is long and packs a lot of lists, but every element (field names, sibling pointer) carries information the agent needs.

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?

With no output schema, the description compensates by spelling out the return contents, and 83% schema coverage handles the six parameters. What is missing is only minor: result ordering/count semantics and how limit interacts with the returned platforms.

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 83%, and the locale currency mapping and query/platform/category meanings are all documented in the schema itself. The description adds no syntax or format detail for limit, max_price, or query beyond what is already there, so baseline 3 applies.

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 ('Search the catalog of ready-made accounts'), names the domain (Telegram, TikTok, Gmail, Steam, ChatGPT and 70+ platforms) and scopes it to comparison across independent shops. It also implicitly separates itself from list_offers, so the agent can pick between them without opening schemas.

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?

The parenthetical '(list_offers sorts one platform or category by price)' gives an explicit alternative and the condition that selects it, and the platform param note 'from earlier results' hints at the follow-up flow. There is no explicit when-not guidance, but the routing to the sibling is clear.

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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