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yarang

Discord Decision MCP

by yarang

discord_read_inbox

Retrieve Discord messages collected by the monitoring daemon to check user communications and notifications from Discord Decision MCP server.

Instructions

Discord inbox에 저장된 메시지를 조회한다.

감시 데몬(discord-watch)이 수집한 Discord 메시지를 조회합니다. Claude Code는 이 Tool을 호출하여 사용자가 Discord에서 보낸 메시지를 확인할 수 있습니다.

Returns: { "success": true, "messages": [ { "message_id": "1234567890", "channel_id": "1234567890", "thread_id": null, "author": "username", "author_id": "1234567890", "content": "메시지 내용", "timestamp": "2024-01-01T00:00:00Z", "read": false } ], "count": 1, "unread_count": 1 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unread_onlyNotrue면 읽지 않은 메시지만 반환, false면 모든 메시지 반환
mark_readNotrue면 조회한 메시지를 읽음으로 표시

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool retrieves messages collected by a monitoring daemon and can return read/unread status. However, it doesn't mention behavioral aspects like rate limits, authentication requirements, potential side effects (e.g., marking messages as read via the mark_read parameter), or error handling. The description adds some context but lacks depth on operational traits.

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?

The description is appropriately sized with three sentences plus a Returns section. The first sentence states the purpose, the second provides context, and the third gives usage guidance. The Returns section is front-loaded but could be integrated more seamlessly. Minimal waste, though the structure slightly separates the output example.

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's moderate complexity (2 parameters, no annotations, but with output schema), the description is fairly complete. It explains what the tool does, its source, and usage context. The output schema in the description details the return format, reducing the need for further explanation. However, it could better address behavioral aspects like side effects or prerequisites.

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

Parameters3/5

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

Schema description coverage is 100%, with both parameters (unread_only, mark_read) well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3. No compensation is needed since schema coverage is complete.

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 tool's purpose: '조회한다' (retrieve/query) messages stored in the Discord inbox. It specifies the source ('감시 데몬(discord-watch)이 수집한 Discord 메시지') and distinguishes it from siblings by focusing on reading inbox messages rather than deleting (discord_delete_message), clearing (discord_clear_inbox), or notifying (discord_notify).

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

Usage Guidelines3/5

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

The description implies usage context: 'Claude Code는 이 Tool을 호출하여 사용자가 Discord에서 보낸 메시지를 확인할 수 있습니다' (Claude Code can call this tool to check messages sent by the user on Discord). However, it doesn't explicitly state when to use this tool versus alternatives like discord_check_pending or provide exclusions. The guidance is present but not comprehensive.

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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