List and filter conversations with human agents. Use status and limit parameters to track task interactions.
列出所有对话
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_conversations"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 返回数量 | |
| status | No | 状态筛选 |
Changes observed during successful MCP inspections.
v1.0.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It only says 'list all conversations' and does not disclose output format, pagination, authorization requirements, or whether this is a read-only operation. The schema provides parameter hints but no behavioral context.
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, short phrase with no wasted words. It is efficient and front-loaded, though it omits useful details.
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?
This is a minimal description for a list tool with no output schema and no annotations. It lacks context about return values, pagination/sorting behavior, and its relationship to sibling tools, making it under-specified for an agent to fully understand its operation.
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 coverage is 100%: limit is described as '返回数量' and status as '状态筛选'. The description adds no additional parameter meaning, so the baseline score of 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 clearly states the action ('list') and the resource ('conversations'), with '所有' indicating all conversations. This distinguishes it from sibling tool get_conversation, which targets a single conversation, and is not a bare tautology.
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?
No guidance is given about when to use this tool vs alternatives such as get_conversation for a single conversation or start_conversation for creating one. The description provides no usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.