list_conversationsRetrieve stored conversations in reverse chronological order, with optional filters for provider, tag, or participant to locate specific conversation history.
Lists stored conversations newest first, optionally filtered by provider, tag, or participant.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | ||
| limit | No | ||
| offset | No | ||
| provider | No | ||
| participant | No |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true, so the description only needs to add behavioral context. It adds ordering (newest first) and filter options, but does not disclose pagination behavior, return format, or whether filters are exact matches. It supplements the annotation with some useful context without contradicting it.
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 a single, front-loaded sentence: 'Lists stored conversations newest first, optionally filtered by provider, tag, or participant.' Every word earns its place, and the primary behavior is stated first with filters appended.
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 five optional parameters, no output schema, and zero parameter descriptions, the description is too sparse. It does not explain pagination (limit/offset), filter matching behavior, return structure, or how it relates to search_conversations. An agent would need to inspect sibling behavior or make assumptions to paginate correctly.
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 must compensate. It names three of the five parameters (provider, tag, participant) as filters, but omits limit and offset entirely, and does not explain their purpose (pagination) or the matching semantics. It adds partial meaning but leaves gaps for the pagination-related parameters.
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 verb (lists), the resource (stored conversations), the ordering (newest first), and optional filters (provider, tag, participant). It distinguishes from get_conversation (single) and search_conversations (search) without needing to name them explicitly.
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 implies this is the listing tool with optional filters, but it does not explicitly state when to use this versus search_conversations or get_conversation. No exclusions or alternatives are mentioned, leaving the agent to infer that list is for browsing and search is for querying.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.