ネット予約のログインを開始する。返されたloginUrlをユーザーに提示し、ブラウザで開いてログインを完了するよう案内すること。このURLは短命かつ一度きりの使い切りであり、他人と共有しないようユーザーに必ず注意喚起すること。ログイン完了後、AIは同じチャット内で予約操作（cancel_reservation等）を再実行してよい。
| 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?
Discloses the one-time, short-lived nature of the loginUrl and instructs warning users not to share it, along with the post-login re-execution behavior; no annotations to contradict.
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?
Concise yet comprehensive; front-loads the purpose and then gives necessary user guidance and warnings. A bit lengthy but each sentence carries essential information.
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?
Provides all necessary operational context: the login flow, URL properties, user instructions, and post-login behavior, despite having no annotations or parameters.
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?
Input schema is empty, so there is no parameter information to add; the mention of loginUrl refers to output, so it neither adds nor misses parameter semantics.
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?
States clearly that the tool starts the login process for online reservations, naming the specific action and resource, and distinguishes itself from reservation and logout tools.
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?
Provides concrete instructions for guiding the user through the loginUrl and notes when to retry reservation operations after login, but does not explicitly state when to call this tool instead of alternatives; still fairly clear.
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 unique, clearly defined purpose: login, logout, search, genres, availability, create, and cancel. No two tools overlap in functionality, making selection straightforward.
All tools follow a consistent verb_noun pattern in snake_case (e.g., search_shops, get_availability, create_reservation). This predictable naming makes the API easy to navigate.
Seven tools neatly cover the necessary operations for an online reservation system without redundancy or bloat. The scope is appropriately focused on the core workflow.
The toolkit covers the essential reservation lifecycle: login, search, availability check, create, cancel, and logout. While an update/modify reservation tool is absent, it is not a typical requirement for this type of system, so the coverage is nearly complete.