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GregBaugues

Token Bowl MCP Server

by GregBaugues

token_bowl_chat_mark_all_messages_read

Marks all chat messages as read across rooms and direct messages in one bulk operation, returning the number of messages updated.

Instructions

Mark all messages as read across all message types.

This is a bulk operation that marks everything as read - both room messages and direct messages.

Returns: Dict containing: - messages_marked_read: Count of messages that were marked as read

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden. It does disclose the key trait that this is a bulk mutation affecting all room and direct messages, plus the return shape, but omits auth/permission requirements, reversibility, and whether it is scoped to the caller. Adequate but incomplete for an unannotated state-changing tool.

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

Conciseness4/5

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

Front-loaded with the action, followed by scope clarification and return value. Mild redundancy between 'across all message types' and 'both room messages and direct messages', but overall efficient and well-ordered.

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?

For a zero-parameter bulk tool with an output schema present, the definition is complete enough to invoke correctly: scope, bulk nature, and return key are all covered. No additional information is strictly required to call it.

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?

The tool takes zero parameters, so the baseline is 4. There is no parameter semantics to add meaning to, and nothing is under-specified on that axis.

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?

States a specific verb+resource ('mark all messages as read') and clarifies the scope ('across all message types', 'both room messages and direct messages'), which distinguishes it from the singular sibling token_bowl_chat_mark_message_read. It never names that sibling explicitly, but the 'all'/'bulk' framing makes the distinction inferable.

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 contains no when-to-use, when-not-to-use, or alternative guidance. It does not mention that the singular token_bowl_chat_mark_message_read exists for targeted reads, leaving the agent to infer selection criteria entirely.

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