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mc_chat_history

Retrieves the most recent chat messages from a running Minecraft instance, including system messages and command output. Optionally returns structured JSON components with formatting details.

Instructions

Get the most recent client-side chat messages — what the user has seen in the chat overlay, including system messages and command output.

Prefer this over walking mc.gui.getChat().allMessages from Groovy (which costs one bridge round-trip per field on each message). Returns {plain, addedTime} per message, newest-first. Set includeJson=true to also receive each message as a structured Component (preserves colors, styles, click events, hover events) — handy for parsing colored command output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax messages returned. Default 50.
includeJsonNoInclude the Component as JSON for each message. Default false.
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return structure ({plain, addedTime} per message), ordering (newest-first), and the effect of includeJson. It does not mention error conditions, rate limits, or authentication, but for a read-only tool with local client data, these omissions are acceptable. The description is transparent about the data and options.

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 concise with no wasted words. It is front-loaded with the main purpose in the first sentence, then provides technical details and usage tips. Every sentence contributes meaningful information.

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 tool's simplicity (2 optional parameters, read-only), the description is complete. It explains what the tool returns (including format), how to control output with parameters, and a practical use case for includeJson. No output schema is needed as the description already covers the return structure.

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?

Schema description coverage is 100%, so baseline is 3. The description adds value by stating the default limit (50) and explaining the purpose of includeJson ('preserves colors, styles, click events, hover events' and 'handy for parsing colored command output'). This goes beyond the schema's descriptions, providing practical usage context.

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 'Get the most recent client-side chat messages' and specifies what is included (system messages, command output). It distinguishes from a potential alternative approach (walking Groovy's getChat) and implies it is the preferred method for this data. The specific verb 'get' and resource 'chat history' make the purpose unambiguous.

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

Usage Guidelines4/5

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

The description explains when to use this tool: when you need recent chat messages. It provides guidance on using includeJson for parsing colored command output. While it does not explicitly exclude other scenarios, it gives clear context and an advantage over a known alternative. There are no sibling tools with similar functionality, so no need for differentiation.

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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