Skip to main content
Glama
thenvoi

Thenvoi MCP Server

Official
by thenvoi

mark_agent_message_failed

Report processing failures in agent messages by recording error details and updating status to failed. Use when an agent cannot complete message processing.

Instructions

Mark a message processing as failed by the agent.

Completes the current processing attempt with an error message.
Call this when the agent cannot process a message.

This endpoint automatically:
- Sets the current attempt's completed_at timestamp (system-managed)
- Sets the current attempt status to "failed"
- Records the error message in the current attempt
- Updates the agent's delivery status to "failed"

Note: Requires an active processing attempt. If no processing attempt exists,
returns a 422 error. Call mark_agent_message_processing first.

Args:
    chat_id: The unique identifier of the chat room (required).
    message_id: The ID of the message to mark as failed (required).
    error: Error message describing why processing failed (required).

Returns:
    Success message confirming the message is marked as failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chat_idYes
message_idYes
errorYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing multiple behavioral traits: it explains what the tool does automatically (sets timestamps, updates statuses, records errors), mentions the prerequisite condition (active processing attempt), and notes the error response (422 if no attempt exists). It doesn't cover rate limits or authentication needs, but provides substantial operational context.

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 efficiently structured with clear sections: purpose statement, usage context, automated behaviors, prerequisites, parameters, and return value. Every sentence adds value, with no redundant information, and it's appropriately sized for the tool's complexity.

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 the mutation nature of the tool (no annotations), 3 parameters with 0% schema coverage, and an output schema present, the description provides complete context. It explains the tool's purpose, when to use it, behavioral effects, prerequisites, parameter meanings, and acknowledges the return value, leaving no significant gaps for agent understanding.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates by explaining all three parameters in the Args section, providing semantic meaning beyond the schema's basic types. It clarifies that chat_id identifies the chat room, message_id identifies the specific message, and error describes why processing failed, adding valuable context not in the schema.

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 the specific action ('mark a message processing as failed') and resource ('by the agent'), distinguishing it from siblings like mark_agent_message_processed and mark_agent_message_processing. It explicitly defines the verb and target, avoiding tautology.

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 provides explicit guidance on when to use this tool ('when the agent cannot process a message'), when not to use it ('requires an active processing attempt'), and names the alternative prerequisite tool ('call mark_agent_message_processing first'). This clearly differentiates it from other message status tools.

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/thenvoi/thenvoi-mcp'

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