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Jaeha0526
by Jaeha0526

kakao_list_chats

Read-only

Retrieve KakaoTalk chat list ordered by recent activity to obtain chat IDs for messaging or reading conversations.

Instructions

List KakaoTalk chats, most recently active first. Start here to get a chat_id.

name is what the KakaoTalk chat list shows: the room title, the open chat's name, the other person for a 1:1 chat, or the member names for an unnamed group. type is "direct", "group", "self" (the user's own memo chat, 나와의 채팅, named after the user) or "unknown" (e.g. open chats). Names aren't unique; if unsure which chat is meant, check members and last_message_at or read a few messages. If the user remembers a phrase, kakao_search(query) returns the chat_id. Some chats may be hidden by the user's config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many chats (max 200).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Beyond the readOnlyHint annotation, the description discloses ordering ('most recently active first'), a caveat about hidden chats, and the meaning of the name and type fields. This adds behavioral detail that helps the agent interpret results and handle edge cases.

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

Conciseness3/5

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

The description is somewhat verbose, with a multi-sentence explanation of name and type fields and string of caveats. While it is well-structured and front-loads the core action, it could be tightened without losing value. It is not overly concise, but not bloated.

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 simplicity (one optional parameter, read-only, with output schema), the description covers the necessary context: what it lists, how to interpret results, and a fallback alternative. It is complete enough for an agent to invoke it correctly and handle results.

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?

The input schema already documents the limit parameter with a description ('How many chats (max 200)'). The tool description does not add additional meaning about the parameter, but since coverage is 100%, the baseline of 3 is appropriate. No extra semantics are needed.

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 a specific verb and resource: 'List KakaoTalk chats, most recently active first.' It also positions the tool as the starting point for obtaining a chat_id, distinguishing it from sibling tools like kakao_search and kakao_read_messages. This is explicit and 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 provides clear usage context: it says to start here for a chat_id, suggests using kakao_search when a phrase is remembered, and advises checking members and last_message_at to disambiguate non-unique names. It does not explicitly list exclusions (e.g., when not to use), but the guidance is strong.

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