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Thenvoi MCP Server

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by thenvoi
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Python
Hybrid

list_agent_messages

List agent messages by status to view pending, processing, processed, or failed items. Retrieve unprocessed messages by default to identify all work the agent should handle.

Instructions

List messages that the agent needs to process, filtered by status.

Default behavior (no status): Returns all messages that are NOT processed.
This is the recommended way to get all work the agent should handle, including
new, delivered, processing (stuck/crashed), and failed messages.

Status filter options:
- (no param): Everything NOT processed - get all work to do
- "pending": No status, delivered, or failed without active attempt - queue depth
- "processing": Currently being processed - in-flight work
- "processed": Successfully completed - done items
- "failed": Failed only - failure backlog
- "all": All messages regardless of status - full history

Messages are returned in chronological order (oldest first).

Workflow after retrieving messages:
1. Get messages via this tool or get_agent_next_message
2. Call mark_agent_message_processing before starting work
3. Process the message
4. Call mark_agent_message_processed or mark_agent_message_failed

Args:
    chat_id: The unique identifier of the chat room (required).
    status: Filter by processing status (optional, default: all actionable).
    page: Page number for pagination (optional).
    page_size: Items per page (optional, default: 20, max: 100).

Returns:
    JSON string containing the list of messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chat_idYes
statusNo
pageNo
page_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.8/5.0
Behavior4/5

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

Without annotations, the description covers default behavior, chronological ordering, and return type (JSON string). It does not mention rate limits, auth needs, or error handling, but provides sufficient context for safe use.

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 with clear sections (default, status options, sorting, workflow, args). Every sentence adds value and it is front-loaded with the main purpose. No wasted words.

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

Completeness5/5

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

Given 4 parameters, no annotations, and an output schema (implied), the description covers filtering, pagination, sorting, and workflow adequately. It explains return value as 'JSON string containing list of messages', which is sufficient.

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?

Input schema has 0% description coverage, so the description fully compensates. It explains each parameter: chat_id required, status options with detailed meanings, page and page_size with defaults and max.

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

Purpose5/5

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

The description clearly states 'List messages that the agent needs to process, filtered by status.' It specifies the resource (agent messages) and action (list). It distinguishes from sibling tool 'get_agent_next_message' by referencing it in the workflow.

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

Usage Guidelines5/5

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

The description explicitly explains default behavior (no status returns actionable messages) and when to use each status filter. It provides a workflow after retrieval, listing alternative tool 'get_agent_next_message' in step 1.

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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