list_capability_requestsReturns the review status and owner notes for this conversation's capability requests.
| Name | Required | Description | Default |
|---|---|---|---|
| conversation_id | Yes | conversation_id returned by start_conversation. | |
| conversation_token | No | conversation_token returned once by start_conversation. Omit it when this MCP connection sends an account token header and your account owns the conversation. |
Changes observed during successful MCP inspections.
Input schema / properties / conversation_token / descriptionPrevious value: -"conversation_token returned once by start_conversation."New value: +"conversation_token returned once by start_conversation. Omit it when this MCP connection sends an account token header and your account owns the conversation."Input schema / requiredPrevious value: -[
- "conversation_id",
- "conversation_token"
-]New value: +[
+ "conversation_id"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds that the payload includes review status and owner notes, which is useful given there is no output schema, but it says nothing about ordering, pagination, or what is returned when no requests exist.
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?
A single sentence with no filler, leading with the return content and scoping it to the conversation. Every element earns its place.
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?
With no output schema, the description partially compensates by naming the returned fields, but it omits the shape of the result, whether it is a collection, and edge cases such as an empty list. For a two-parameter read tool with full schema coverage this is adequate but leaves clear gaps.
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%, with conversation_id and conversation_token both documented, including the conditional omission guidance for the token. The description only restates 'this conversation's' scoping, adding no meaning beyond the schema, 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?
The description uses a concrete verb ('Returns') and names the specific payload: review status and owner notes for this conversation's capability requests. It is scoped to a single conversation, which distinguishes it from broader listing tools. It does not, however, differentiate itself from the sibling get_capability_request_status.
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?
There is no statement of when to use this versus get_capability_request_status (single request status) or the various request_* tools that create requests. The name implies a listing operation, but the description offers no conditions, prerequisites, or exclusions.
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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