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ticktick_get_unprocessed_completions

Fetch unprocessed completed tasks from a TickTick project to identify new completions for handling at conversation start.

Instructions

Returns completed tasks for a project that have NOT yet been marked as processed by a domain agent.

Could be called at the beginning of each conversation to check for new completions. After reviewing each returned task, call ticktick_mark_completion_processed to record that it has been handled.

Args: project_id (str): TickTick project ID or name to check. Required. Accepts the project's name as well as its ID (case-insensitive, trimmed; "Inbox" resolves to the inbox). Two projects sharing a name is an error, not a guess. days (int): How many days back to look for completions. Default 30.

Returns: JSON list of unprocessed task objects (may be empty). Each object includes: id, title, projectId, completedTime, content. Error: {"error": "...", "status": "error"}

Usage Guide: - Call once per project at the start of each conversation. - For each returned task: read the content field, log meaningful outcomes if appropriate, then call ticktick_mark_completion_processed. - Example: ticktick_get_unprocessed_completions( project_id="your_project_id_here", days=30 )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully discloses behavior: it is a read-only retrieval operation, returns unprocessed tasks, does not mark them as processed itself, and specifies error output format. It also explains edge cases like duplicate project names and case-insensitive name resolution. This exceeds expectations given the absence of annotations.

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 well-structured with clear sections (Args, Returns, Usage Guide) and a concise opening statement. While slightly verbose, every sentence adds meaningful information, and the example makes invocation explicit without redundancy.

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 tool's moderate complexity, no annotations, and the presence of an output schema, the description still adds essential context: the return item fields, error format, and the required follow-up action. It fully prepares an agent to invoke the tool correctly and interpret its results.

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?

The input schema only provides names and types, but the description adds critical semantics: project_id accepts either ID or name, supports case-insensitive trimmed matching, resolves 'Inbox', and raises an error on ambiguous name collisions. It also explains the days parameter's meaning and default. This optimally compensates for the 0% schema description coverage.

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 uses a specific verb+resource ('Returns completed tasks for a project...') and clearly distinguishes the tool from siblings by emphasizing the 'NOT yet marked as processed' state. It also mentions the workflow with ticktick_mark_completion_processed, which sets it apart from generic task-listing tools.

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

Usage Guidelines5/5

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

It explicitly states when to call it ('at the beginning of each conversation'), which sibling to use afterward (ticktick_mark_completion_processed), and includes a step-by-step Usage Guide with an example invocation. This leaves no ambiguity about the intended usage 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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