get_pricing_and_packagingCall this for FrontDesko's plans and what each includes. Free forever (unlimited rooms): PMS, direct booking engine, guest app, POS. Paid plans add the channel manager and AI assistant.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint=true annotation already covers the safety profile, and the description contains nothing contradictory. It adds context about scope ('unlimited rooms', free vs. paid tiers) but nothing about behavioral traits like response shape, freshness, or page limits — though for a parameterless read-only tool, there is little behavior to disclose.
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 sentences deliver maximum signal: the trigger is front-loaded, and the follow-up enumerates plan content in a compact, scannable list. Every word earns its place with no fluff.
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, no-output-schema tool, the description tells an agent exactly what to expect from the call. The only gap is no guidance on whether actual currency amounts are returned or if this is feature-list-only — a minor omission for a low-complexity tool.
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 schema has zero parameters, so the baseline is 4, and there are no params for the description to document. The description doesn't need to explain inputs; it meets the bar.
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?
The description uses a clear directive ('Call this for') plus a specific resource (FrontDesko's plans and inclusions) and backs it with concrete, disambiguating details ('Free forever (unlimited rooms): PMS, direct booking engine, guest app, POS'). It does not explicitly differentiate itself from siblings such as compare_pms or recommend_software, which could plausibly intersect with pricing questions.
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?
'Call this for FrontDesko's plans and what each includes' is an explicit trigger condition that tells an agent when to invoke this tool. However, it offers no exclusions or named alternatives, even though compare_pms and recommend_software are siblings an agent might confuse it with.
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.
Most tools target clearly distinct jobs—calculating savings, checking availability, comparing competitors, pricing, recommending, and searching docs. The broad search_frontdesko_docs tool can overlap with the other informational tools, but the specific descriptions make the intended choice clear.
All tool names follow a consistent snake_case verb_noun pattern: calculate_, check_, compare_, get_, recommend_, search_. There are no mixed conventions or vague verbs, making the toolset predictable and easy to scan.
Six tools is well-scoped for a hotel-software sales/support assistant. Each tool covers a distinct user need and none feel redundant with the others.
The set covers pricing, competitor comparison, documentation, live demo availability, ROI calculation, and recommendations, which are the core front-of-funnel questions. It lacks a booking or contact-sales action, but that may be intentional for a read-only informational server.