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todoist_create_personal_label

Create custom labels in Todoist to organize tasks by adding names, colors, and priorities for personal categorization.

Instructions

Create one or more personal labels in Todoist

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelsNoArray of labels to create (for batch operations)
nameNoName of the label
colorNoColor of the label (optional)
orderNoOrder of the label (optional)
is_favoriteNoWhether the label is a favorite (optional)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates labels but lacks critical details: it doesn't specify whether this is a write operation (implied but not explicit), what permissions are required, if there are rate limits, how errors are handled, or what the return value looks like (no output schema). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core purpose ('Create one or more personal labels in Todoist') with zero wasted words. It's appropriately sized for a tool with a well-documented schema, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (a mutation operation with 5 parameters, no annotations, and no output schema), the description is incomplete. It doesn't address behavioral aspects like authentication needs, error handling, or return values, which are crucial for an agent to invoke it correctly. The high schema coverage helps with parameters, but the overall context for safe and effective use is lacking.

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 fully documents all 5 parameters, including optionality, data types, and enum values for color. The description adds no parameter-specific information beyond implying batch capability ('one or more'), which is already covered by the 'labels' array parameter in the schema. This meets the baseline of 3 when the schema does the heavy lifting.

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?

The description clearly states the action ('Create') and resource ('personal labels in Todoist'), specifying it can handle batch operations ('one or more'). It distinguishes from sibling tools like todoist_update_personal_label or todoist_get_personal_labels by focusing on creation. However, it doesn't explicitly differentiate from todoist_create_project or todoist_create_task, which are similar creation operations for different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication needs), when to use batch vs. single creation, or how it differs from related tools like todoist_update_personal_label for modifications. The agent must infer usage from the tool name and schema alone.

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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