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Batch Create Tasks

dida365_batch_create_tasks

Create multiple tasks in one request to add many items to a project at once, reducing separate API calls.

Instructions

Batch create multiple tasks in one request.

Each dict requires "title" and "projectId". Optional fields same as create_task. Returns {"id2etag": {...}, "id2error": {...}}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, non-idempotent, openWorld). The description adds genuinely useful behavior beyond them: the return shape {'id2etag','id2error'} discloses that this is a partial-failure batch operation where individual tasks can fail independently — important context for a non-idempotent write.

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?

Three short sentences, zero filler, with the core purpose front-loaded and the return contract last. Every sentence earns its place by supplying information absent from the structured fields.

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?

For a 1-param batch mutation tool, the description covers purpose, required item fields, and the partial-failure return contract, and an output schema exists so return values need no further explanation. It could be more complete by noting ordering limits or whether the request is atomic, but nothing essential to invoking it correctly is missing.

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 coverage is 0% and the single 'tasks' param is an opaque array of additionalProperties:true objects, so the description carries the full burden. It specifies that each dict requires 'title' and 'projectId' and that optional fields match create_task, which meaningfully compensates. It loses a point only because it defers field details to another tool's schema rather than listing them.

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?

States a specific verb+resource+scope: 'Batch create multiple tasks in one request.' The word 'batch'/'multiple' cleanly separates it from the single-task sibling create_task without needing to name it. It stops just short of explicit sibling routing, so a 4 rather than 5.

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?

Usage is implied by 'Batch create multiple tasks in one request' — an agent can infer this is the bulk variant — but there is no explicit when-to-use/when-not guidance and no mention of alternatives like create_task. The reference to create_task is for field definitions, not for routing decisions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.