Skip to main content
Glama

workers_chats_list

List user chats from AI workers, with optional group filtering and result limits for efficient conversation management.

Instructions

List user chats (no message logs).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
group_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only reveals that message logs are excluded, but omits other critical traits such as ordering, pagination behavior, rate limits, handling of empty results, or any authentication requirements. The single behavioral trait is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at five words, but this brevity comes at the cost of completeness. It front-loads the core action but fails to include essential details about parameters, behavior, or output. True conciseness balances brevity with informativeness; this description is underspecified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema and two parameters, the description is only five words and does not explain the semantics of the parameters, the structure of the output, or any edge cases. The sibling tools provide some context, but the description itself is too sparse to be considered complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the input schema provides no descriptions for the parameters 'limit' and 'group_id'. The tool description does not add any meaning beyond the parameter names and default values. An agent cannot infer the purpose of 'group_id' or how 'limit' interacts with the result set from the description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List user chats (no message logs)' clearly states the verb (list) and resource (user chats). It distinguishes from sibling tools like workers_chats_get and workers_chat_send by explicitly excluding message logs, which is a helpful differentiator. However, it does not elaborate on what constitutes a 'user chat' in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as workers_chats_get or workers_chat_send. It does not specify prerequisites, limitations, or exclusive scenarios. The only hint is the exclusion of message logs, which implicitly suggests using this tool when logs are not needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dimaneuron/aiworkers-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server