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ticktick_update_task

Updates a TickTick task by overlaying only the fields you explicitly set, preserving all other existing data to prevent accidental erasure.

Instructions

Update an existing task without wiping unmodified fields.

The TickTick API requires the entire editable task on every update; any omitted field is wiped server-side. To prevent that we fetch the current task, then overlay ONLY the fields the caller explicitly set (exclude_unset=True).

Args: task_object (TaskObject): Must include id. All other fields are optional; set only the ones you want to change. When dueDate is set you must also set expectedDayOfWeek.

Returns: JSON object containing the updated task. _verification_warnings is attached if the response did not match what we sent. On failure: {"error": "...", "status": "error"}.

Limitations: - Read-only API fields (creator, etag, createdTime, modifiedTime, deleted, kind, isFloating) are stripped before the call.

Agent Usage Guide: - To reschedule a task, send a single update with the new dueDate + expectedDayOfWeek. Do NOT complete and recreate.

Example: ticktick_update_task(task_object={ "id": "60ca9dbc8f08516d9dd56324", "projectId": "", "priority": 5, "dueDate": "2026-06-15T20:45:00+01:00", "expectedDayOfWeek": "Monday", "timeZone": "Europe/London", })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_objectYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, so description carries full burden. It details the fetch-and-overlay mechanism, read-only field stripping, return format with verification warnings, and the validation-only nature of expectedDayOfWeek.

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?

Structured with Args, Returns, Limitations, Agent Usage Guide, and Example. Each section adds value, though slightly long. Well-organized and front-loaded with key behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of partial updates and read-only fields, the description covers all necessary behaviors: edge cases (dueDate+expectedDayOfWeek), return format, failure mode. Output schema exists, so return explanation is sufficient.

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?

Schema description coverage is 0%, so description compensates: explains task_object requires id, optional fields, and the dueDate+expectedDayOfWeek constraint. Example demonstrates usage. Could list more fields but schema already defines them.

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 updates an existing task without wiping unmodified fields, explaining the underlying API behavior. It distinguishes from sibling tools like delete, create, and complete by focusing on partial updates.

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 'Agent Usage Guide' provides explicit advice, such as rescheduling via a single update with dueDate and expectedDayOfWeek. It does not explicitly state when not to use, but the context is sufficiently clear.

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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