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Doist

Twist AI MCP Server

Official
by Doist

mark-done

DestructiveIdempotent

Mark threads or conversations as done to organize your inbox—by specific IDs or bulk across a workspace or channel. Mark as read, archive, or clear unread markers.

Instructions

Mark threads or conversations as done. Supports individual IDs or bulk operations (mark all in workspace/channel). For threads: can mark as read, archive in inbox, or clear all unread. For conversations: can mark as read and archive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoSpecific thread or conversation IDs to mark as done. Use this OR bulk selectors.
typeYesThe type of items to mark as done: thread or conversation.
archiveNoArchive items in the inbox (threads only, default: true).
markReadNoMark items as read (default: true).
channelIdNoMark all threads in this channel as done (threads only).
clearUnreadNoClear all unread markers for workspace (threads only, requires workspaceId, default: false).
workspaceIdNoMark all threads in this workspace as done (threads only).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
typeYes
failedYes
itemTypeYes
completedYes
selectorsNo
operationsYes
failureCountYes
successCountYes
totalRequestedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv7.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv5.5.1

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=false, destructiveHint=true, and idempotentHint=true. The description adds meaningful context by specifying what 'mark done' actually does: mark as read, archive, and clear unread. It does not contradict annotations and discloses the mutating behaviors beyond what the structured fields alone provide.

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 three sentences, front-loaded with the core action, and every sentence adds useful information. There is no filler or redundancy.

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?

The schema covers all parameters and an output schema exists, so the description does not need to explain return values. It explains the major behavioral modes and per-type differences. It slightly undersells how the bulk selectors combine with flags, but overall it is sufficiently complete for correct invocation.

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%, so the schema already documents each parameter. The description restates the higher-level intent of ids, channelId, workspaceId, and the boolean flags, but it does not add semantic detail beyond what the input schema already provides.

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 verb and resource: mark threads or conversations as done. It also distinguishes the main modes (individual IDs vs bulk workspace/channel) and the per-type behaviors, making the tool's purpose clear even among siblings like delete-object and update-object.

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 gives clear usage context: individual IDs versus bulk selectors, and thread-specific versus conversation-specific operations. It does not explicitly name alternatives or when-not-to-use cases, but the intended usage is well implied.

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