send_room_messageSend a first message to the landlord of an approved available room from the authenticated UniAffitti account. The conversation is stored in the same UniAffitti chat used by the web app.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| room_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false and destructiveHint=false. The description adds meaningful behavioral context beyond annotations by specifying that the conversation is stored in the same UniAffitti chat used by the web app, and that the action originates from the authenticated account.
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 two tight sentences with no filler. It front-loads the core action immediately and adds the storage detail as a second sentence, earning every word.
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?
The description covers the essential context: the action, the target, the precondition, authentication, and persistence. There is no output schema and no return-value description, but for a simple send-message tool the description is nearly complete.
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 0%, so the description needs to compensate by explaining room_id and message. It does imply that room_id refers to an approved available room and message is the first message content, but it never explicitly maps or describes the parameters, leaving much of the semantics to inference from property names.
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 states a specific verb and resource: it sends a first message to the landlord of an approved available room. It further narrows the scope with the authenticated UniAffitti account and the approved/available preconditions, making it clearly distinct from sibling tools like get_room_details or create_rental_request.
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 phrase 'first message' and 'approved available room' gives clear context for when this tool should be used. It does not explicitly name alternatives or state when not to use it, but the intended scenario is unambiguous enough for an agent to select it correctly.
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 are distinct by resource and action, but the search/catalog cluster is fuzzy: search_universities, search_cities, list_search_metadata, and list_university_campuses overlap in purpose. search_rooms and rank_room_matches also have a similar discovery role, making it easy to select the wrong tool without careful reading.
All tool names follow a consistent snake_case verb_noun pattern, with verbs like add, list, get, search, create, update, and send clearly indicating the action. This makes the tool surface highly predictable and easy to navigate.
20 tools is on the heavier side, but the count is justified by the broad scope: room search, comparison, ranking, favorites, rental requests, messaging, listing creation, and university catalog browsing. The set remains manageable because each tool maps to a distinct workflow step.
Core room-finding workflows are covered well: search, details, compare, favorites, requests, and messages. However, listing management is incomplete (create_listing has no update/delete) and messaging only supports sending a first message, with no tool for replying to an existing conversation, leaving notable dead ends.