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thenvoi

Thenvoi MCP Server

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by thenvoi

list_user_peers

Discover available users and agents for chat interactions, with options to filter by type or exclude existing participants.

Instructions

List entities you can interact with in chat rooms.

Peers include other users, your agents, and global agents.

Args:
    not_in_chat: Exclude entities already in this chat room (optional).
    peer_type: Filter by type: 'User' or 'Agent' (optional).
    page: Page number (optional).
    page_size: Items per page (optional).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
not_in_chatNo
peer_typeNo
pageNo
page_sizeNo

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 full burden for behavioral disclosure. It states this is a listing operation (implied read-only) and mentions pagination parameters, but doesn't cover important aspects like authentication requirements, rate limits, error conditions, or what the output contains. The description is insufficient for a tool with 4 parameters and no annotation coverage.

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

Conciseness5/5

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

The description is well-structured and appropriately sized. It begins with a clear purpose statement, defines the scope of 'peers', then provides a formatted parameter section. Every sentence earns its place, with no redundant or unnecessary information.

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

Completeness4/5

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

Given the tool has an output schema (which handles return values), 4 parameters with good semantic coverage in the description, and moderate complexity, the description is reasonably complete. The main gap is the lack of behavioral context (auth, errors, etc.) and usage guidance relative to sibling tools, but the parameter documentation and clear purpose make it functional.

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

Parameters5/5

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

The description provides excellent parameter semantics through the 'Args:' section that explains all 4 parameters in plain language. With 0% schema description coverage (titles only, no descriptions), this documentation is essential and fully compensates for the schema gap. Each parameter's purpose is clearly explained beyond the basic titles in the schema.

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 clearly states the tool's purpose: 'List entities you can interact with in chat rooms' and specifies what peers include ('other users, your agents, and global agents'). This provides a specific verb ('List') and resource ('entities/peers'), though it doesn't explicitly differentiate from sibling tools like 'list_agent_peers' or 'list_user_chat_participants' beyond the name.

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. It doesn't mention sibling tools like 'list_agent_peers' (for listing agent peers specifically) or 'list_user_chat_participants' (for listing participants already in a chat), nor does it explain prerequisites or appropriate contexts for use.

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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