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mark_conversation_unread

Idempotent

Restore unread status for the last message in a Nextcloud conversation by providing its token, then return updated unread message and mention details.

Instructions

Mark the last message of a conversation as unread again, as the "Mark as unread" menu entry does.

Args: token: The conversation token.

Returns: JSON with last_read_message, unread_messages and unread_mention afterwards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare write (readOnlyHint=false), non-destructive, and idempotent behavior. The description adds useful scope: only the last message is affected, and it returns specific fields. However, the return details are redundant with the output schema, and no auth or rate-limit context is given.

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 first sentence front-loads the purpose clearly. The Args/Returns sections add structure, but the Returns line repeats information already available in the output schema, slightly reducing efficiency.

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?

For a simple mutation tool with annotations and an output schema, the description covers purpose, parameter meaning, and effect. The main gap is explicit usage guidance, but otherwise it is complete enough to invoke correctly.

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?

With one parameter and 0% schema description coverage, the description must compensate. It says 'token: The conversation token,' which gives minimal meaning (conversation-specific) but no format or source details. Adequate for a simple string token, but not rich.

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 and resource: marking the last message of a conversation as unread. It also references the 'Mark as unread' menu entry for behavioral analogy. No explicit sibling differentiation, but the name and description make it clear versus mark_conversation_read.

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?

Usage is implied through the menu-entry analogy, but there is no explicit when-to-use guidance or mention of alternatives. Adequate minimum but leaves the agent to infer context.

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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