Post a message to the session. Use for buyer questions, AI analysis notes, or responses. The dealer and other AI agents can see these.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Message content | |
| session | Yes | Session hash | |
| agent_id | No | Your agent identifier | |
| msg_type | No | Type: note, question, answer, offer, alert | note |
| from_role | No | Role: buyer, ai, or system | ai |
| vehicle_vin | No | Optional: which vehicle this is about |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the message is visible to the dealer and other AI agents, which is useful behavioral context. It also clearly implies a write operation. However, it does not mention any potential side effects, such as whether the message is appended or if there are permission requirements. This is adequate for a simple messaging tool but not exhaustive.
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 three concise sentences, each adding value: the action, the use cases, and the visibility. It is front-loaded and free of 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?
The tool is simple, the schema covers all parameters, and the description provides purpose and use cases. No output schema exists, so return values need not be explained. The description is complete enough for an agent to use the tool correctly, though it could mention potential limitations or side effects.
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%, meaning every parameter already has a description in the input schema. The tool description adds no additional parameter-level detail. Baseline for high coverage is 3, which 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 clearly states the tool's function with a specific verb and resource: 'Post a message to the session.' It also gives example use cases. However, it does not explicitly differentiate from sibling tools like cars_session_reply, leaving some ambiguity about when to post vs. reply.
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 provides explicit use cases: 'Use for buyer questions, AI analysis notes, or responses.' This indicates when the tool is appropriate. It does not mention when not to use it or alternatives, but the guidance is clear enough for an AI agent to make a reasonable decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools target distinct resources (dealer inventory, vehicle search, session actions), but cars_session_message and cars_session_reply have overlapping purposes as both involve posting messages. The session tools are otherwise clearly differentiated by their action verbs.
All tools share the 'cars_' prefix and use snake_case, but the verb-noun pattern is inconsistent: some are action-first (cars_search, cars_session_create) while others are noun-only (cars_vehicle, cars_dealers, cars_history). Session tools follow a consistent 'session_<verb>' structure, but the broader set mixes conventions.
With 19 tools, the set is on the heavy end, falling in the 16-25 range that feels borderline. The count is justified by the comprehensive session workflow, but it approaches the threshold where tool selection becomes cumbersome.
The core journey of searching, inspecting, and tracking vehicles through sessions is well covered, including dealer communication and trade-in. However, there are notable gaps: no way to remove a vehicle from a session or update general buyer profile details (payment method, timeline) after initial creation.