Get Areas
get-areasRetrieve all project areas from the Things 3 app on macOS to organize tasks and manage workflows.
Instructions
Get all areas from Things. Uses AppleScript (macOS only).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get-areasRetrieve all project areas from the Things 3 app on macOS to organize tasks and manage workflows.
Get all areas from Things. Uses AppleScript (macOS only).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, indicating a safe read operation. The description adds value by specifying the implementation method ('Uses AppleScript') and platform constraint ('macOS only'), which aren't covered by annotations. However, it lacks details on return format, error handling, or other behavioral traits, so it only partially compensates for the absence of richer annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences: one stating the purpose and one adding implementation context. Every word earns its place, and it's front-loaded with the core functionality, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, read-only operation) and lack of output schema, the description is adequate but could be more complete. It covers purpose and platform constraints but doesn't explain what 'areas' are in the Things context or what the return data looks like, leaving some gaps for an AI agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the schema fully documents the input (none required). The description doesn't need to add parameter details, so it meets the baseline for this scenario. No additional semantic information is provided or needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get all areas') and resource ('from Things'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'get-projects' or 'get-todos' beyond specifying the resource type, which is why it doesn't reach a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context with 'Uses AppleScript (macOS only)', suggesting platform restrictions, but doesn't explicitly state when to use this tool versus alternatives like 'get-projects' or 'get-todos'. No guidance on prerequisites or exclusions is provided, leaving usage somewhat ambiguous.
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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