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Update a task

update_task
Destructive

MUTATES Parabol data: update an existing task. Required: id. Optionally change content (stringified TipTap JSON), status, assignee (userId), or sortOrder. Only included fields change. Parabol GraphQL: updateTask(updatedTask, area). Requires TASKS_WRITE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe task id (required).
areaNoOptional AreaEnum context.
fieldsNoAdditional documented GraphQL input fields to send verbatim in this mutation's input (merged OVER the typed fields above).
statusNoNew status (TaskStatusEnum).
userIdNoReassign the task to this user id.
contentNoNew rich-text content as a stringified TipTap/ProseMirror JSON document.
sortOrderNoNew sort order (Float).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already flag destructiveHint=true, and the description reinforces and extends this with 'MUTATES', partial-update semantics, and an explicit TASKS_WRITE permission requirement. It does not speculate about irreversibility or side effects, but for an update tool the key behavioral warnings are disclosed.

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?

Two dense sentences front-load the mutation warning, then cover required id, optional fields, partial-update behavior, GraphQL mapping, and authorization. No filler or repetition.

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 mutation with one required param and several optional fields, the description gives the essential context: what changes, what stays untouched, and what permission is needed. The lack of an output schema is a minor gap, but the schema and annotations cover the remaining mechanics.

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?

Input schema covers 100% of parameters, so the baseline is 3; the description adds the human-readable alias 'assignee (userId)' and clarifies that only included fields are changed, which is useful beyond the raw schema. The area and fields parameters are left to the schema, but they are fully documented there.

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 opening phrase 'MUTATES Parabol data: update an existing task' gives a specific verb, resource, and mutation type, and 'Required: id' distinguishes this from sibling creation tools like create_task. The title confirms what the tool does, and the description makes the scope (existing task, partial update) unmistakable.

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 implies when to use it: when you have an existing task id and want to change only the supplied fields, with 'Only included fields change' preventing accidental overwrites. It does not name alternatives explicitly, so it stops short of a 5.

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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TDQS

A4/5.0
Disambiguation5/5

Every tool targets a distinct resource and action: get_/list_ tools are clearly separate read paths, create_/update_/start_/add_ tools map to distinct mutations, and the two escape hatches are explicitly labeled. Even near neighbors like list_meetings and list_active_meetings are unambiguous.

Naming Consistency4/5

Most tools follow a consistent pattern: list_/get_ for reads, create_/update_/start_ for mutations, with plural nouns for collections and singular for single resources. Minor deviations like add_comment, invite_to_team, and the parabol_* escape hatches prevent a perfect score.

Tool Count3/5

With 21 tools, the server sits in the 16-25 range that feels heavy for an MCP surface. The breadth is somewhat justified because Parabol spans organizations, teams, meetings, tasks, and comments, but many tools are list/get variants of the same core entities.

Completeness3/5

Core read and write flows exist for teams, organizations, meetings, tasks, and comments, but there are notable lifecycle gaps such as no delete_task, no reflection update/delete, and no meeting end/update mutations. The parabol_graphql and parabol_query escape hatches help work around these gaps but do not make the curated surface fully complete.