Prüft ob Blumen Komander München an einem bestimmten Datum in eine bestimmte PLZ liefern kann. Lieferung ist bei Blumen Komander immer kostenlos - keine Liefergebühr. Gibt Same-Day Cutoff zurück.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Lieferdatum im Format YYYY-MM-DD | |
| postalCode | No | Ziel-Postleitzahl in München (z.B. 80799) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds useful behavioral context: delivery is always free and a same-day cutoff is returned. However, it does not disclose whether the operation is read-only, what happens when delivery is unavailable, or any error conditions, leaving some transparency gaps.
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?
The description is compact (three short sentences) and each sentence adds value: the core purpose, the free-delivery fact, and the return value. There is no filler or 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?
With no output schema, the description does mention the returned same-day cutoff, which helps. However, it does not fully describe the response shape or how availability is indicated (e.g., boolean, message). Given the simplicity of the tool, this is a minor gap and the description is otherwise complete enough for a basic check.
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?
Schema description coverage is 100% for the two parameters (date and postalCode). The description restates these concepts but adds no new parameter-level meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 specific verb 'prüft' (checks) with a clear resource (delivery capability of Blumen Komander München) and scoping parameters (date and postal code). It also mentions the return of a same-day cutoff, making it distinctly different from sibling tools like create_cart or get_order_status.
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 makes it clear this is a pre-order availability check, but it does not explicitly name when not to use it or mention alternative tools. No exclusions are stated, and the context is clear enough for basic guidance.
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 has a clear, distinct purpose: checking delivery availability, creating a cart, getting a checkout link, tracking an order, obtaining shop info, and searching for bouquets. No two tools overlap in functionality, making it easy for an agent to select the correct one.
All tool names follow a consistent verb_noun pattern in snake_case: check_availability, create_cart, get_checkout_link, get_order_status, get_shop_info, search_flowers. The naming is uniform and predictable.
With 6 tools, the set is well-scoped for a flower ordering service. Each tool covers an essential step in the customer journey without unnecessary redundancy, and the count is within the ideal range for an MCP server.
The tool set covers the full ordering lifecycle: searching for flowers, checking delivery availability, creating a cart with all necessary details, obtaining a checkout link for payment, and tracking order status. There are no obvious gaps or dead ends in the flow.