Mark a conversation read
mark_conversation_readClear a conversation's unread mark, as opening it in the app does.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| conversationId | Yes | Conversation id from list_conversations. |
mark_conversation_readClear a conversation's unread mark, as opening it in the app does.
| Name | Required | Description | Default |
|---|---|---|---|
| conversationId | Yes | Conversation id from list_conversations. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the mutation profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=false). The description adds genuine behavioral context beyond them: the effect is exactly the user-visible 'opened' state, which reinforces why the call is idempotent and non-destructive. It stops short of noting auth requirements or whether the change is reversible, keeping it out of the top band.
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?
One short sentence that front-loads the action and its object, with the app-opening analogy tacked on as clarifying context. Nothing is wasted and nothing needs reordering.
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?
For a single-parameter, non-destructive, idempotent toggle with a fully documented schema and a complete annotation set, the description covers what an agent needs. Only marginal gaps remain (no mention of permission requirements or behavior when the conversation is already read).
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% and the single parameter already carries the useful hint 'Conversation id from list_conversations.' The description adds no syntax, format, or sourcing detail beyond that, so the baseline 3 applies.
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 a specific verb and resource ('Clear a conversation's unread mark'), which pins down exactly what state changes and on which object. The resource naming implicitly separates it from sibling noise such as mark_notification_read and mark_all_notifications_read, so an agent can pick it without opening the schema.
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 analogy 'as opening it in the app does' implies the intended usage context, but the description never states when to call this versus alternatives (e.g. update_conversation, snooze_conversation) or any preconditions. Usage is implied rather than explicit.
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.