list_services
List purchasable Instagram and TikTok services, quantity limits and starting prices in integer CZK halere. Use get_quote for an exact price.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List purchasable Instagram and TikTok services, quantity limits and starting prices in integer CZK halere. Use get_quote for an exact price.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, idempotent, openWorld, and non-destructive behavior. The description adds useful context that only starting prices are provided and prices are in integer CZK halere, plus a pointer to get_quote for exact amounts. However, it does not describe return format or pagination, so the added value beyond annotations is modest.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, with the main action and output details front-loaded in the first sentence and the cross-reference to get_quote placed cleanly in the second. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only list tool with annotations covering safety and open-endedness, the description provides all essential facts: what is listed, the included fields, the currency unit, and how to obtain exact prices. No critical information is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema properties are empty, so there are no parameter semantics for the description to clarify. The baseline of 4 applies because there is nothing to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses the specific verb 'List' and names the precise resource ('purchasable Instagram and TikTok services') with key output details ('quantity limits and starting prices'). It also differentiates itself from the sibling get_quote by explicitly pointing out that exact pricing is obtained through that other tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent this tool is for listing purchasable services with their limits and starting prices, and explicitly directs to get_quote when an exact price is needed. This provides a clear condition for choosing an alternative, satisfying the when/when-not requirement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a distinct resource or action: profile lookup, post listing, service listing, quoting, order creation, payment, order status, and wallet balance. The only adjacent pair is list_services/get_quote, but their descriptions explicitly separate catalog pricing from exact quote calculation.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_* for single resources, list_* for collections, and create_order/pay_order for lifecycle actions. No mixed naming conventions or vague verbs appear.
Eight tools is well-scoped for a social media engagement purchasing server. Each tool covers a necessary step in the quote-to-delivery workflow without redundancy or unnecessary surface area.
The tool set covers the full lifecycle: discover services, inspect profiles/posts, get a verified quote, create an unpaid order, check wallet balance, pay, and track order status. No critical gap prevents an agent from completing the intended purchase flow.