link_accountStartet die Verknuepfung eines Kundenkontos: liefert eine Login-URL (fuer den Kunden im Browser) und ein session_token. Nach dem Login im Browser koennen list_orders/get_loyalty/request_address_change mit diesem token genutzt werden.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry full burden for behavioral disclosure. It mentions the output (URL and token) and subsequent tool usage, but lacks details about side effects (e.g., does it create a persistent session?), auth requirements, rate limits, or token expiration. This leaves significant 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 a single sentence with two concise clauses, front-loaded with the primary action. Every word adds value; no redundancy or 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?
Given the tool has no input schema, output schema, or annotations, the description covers the essential purpose, output, and usage context with sibling tools. However, it omits details like token lifetime or prerequisites, which would enhance completeness.
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?
There are no parameters (0 params), so schema coverage is 100% with no detail needed. Baseline is 4 for zero parameters. The description adds context about the output, which is relevant but not parameter semantics per se.
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 clearly states the tool initiates account linking, returning a login URL and session token. It distinguishes from sibling tools like list_orders and get_loyalty by indicating they can be used after the linking step.
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 explains that after login in the browser, the session token can be used with specific sibling tools, providing clear context for when to use this tool (before those tools). It does not explicitly state when not to use it, but the guidance is sufficient.
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 targets a distinct function: inventory checks, cart creation, product search, order management, loyalty, support. No overlap among search_products, list_products, and get_product; similarly, list_orders and request_address_change are unique.
All tools follow a verb_noun pattern (e.g., check_availability, create_cart, link_account) with consistent snake_case and English verbs, even though the shop is German. No mix of conventions.
19 tools is slightly above the typical 3-15 range for a focused server, but the number is justified by the breadth of shop functionality (product browsing, orders, cart, loyalty, guides, support). Not excessive.
Covers core shopping flows: product discovery, cart creation, order tracking, and account linking. However, missing tools for cart modification (add/remove items), order cancellation/returns, and checkout. These gaps may cause agent failures.