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update_project

Update an existing project in Things by modifying its title, notes, schedule, deadline, tags, completion status, or moving it to a different list or area.

Instructions

Update an existing project in Things.

Args:
----
    id: ID of the project to update
    title: New title
    notes: New notes
    when: New schedule (today, tomorrow, anytime, someday, or YYYY-MM-DD)
    deadline: New deadline (YYYY-MM-DD)
    tags: New tags. IMPORTANT: Always pass as an array of strings (e.g., ["tag1", "tag2"]) NOT as a comma-separated string. Passing as a string will treat each character as a separate tag.
    completed: Mark as completed
    canceled: Mark as canceled
    list_name: Move project directly to a built-in list. Must be one of:
              - "Today": Move to Today list
              - "Anytime": Move to Anytime list
              - "Someday": Move to Someday list
              - "Trash": Move to trash
              Note: Projects cannot be moved to Inbox or Logbook. To move a project
              to Logbook, mark it as completed instead.
    area_title: Title of the area to move the project to
    area_id: ID of the area to move the project to

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
tagsNo
whenNo
notesNo
titleNo
area_idNo
canceledNo
deadlineNo
completedNo
list_nameNo
area_titleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description bears full burden. It includes important behavioral notes: tags must be array not string, list_name restrictions (cannot move to Inbox/Logbook), and how to move to Logbook via completed. However, it does not disclose error behavior or return value details.

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 description is front-loaded with purpose and uses a structured 'Args' section. It is slightly verbose due to detailed parameter notes, but every sentence adds value.

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?

Despite 11 parameters and no annotations, the description covers all parameters with behavioral constraints. It lacks information about what happens on invalid id or error conditions, but output schema likely handles return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining each parameter's meaning. It provides valid values for 'when', warns about 'tags' array format, enumerates allowed 'list_name' values, and clarifies area parameters.

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 'Update an existing project in Things,' specifying the verb (update) and resource (project). It distinguishes from sibling tools like add_project (create) and update_todo (update todos), making the purpose unambiguous.

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?

The description does not explicitly state when to use this tool vs alternatives like add_project. It provides some parameter-specific guidance (e.g., list_name constraints) but lacks general when-to-use 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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