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task_batch_undrop

Restore multiple canceled OmniFocus tasks to active status in one batch. Atomic validation rejects invalid input; execution is best-effort with per-index success or failure reports.

Instructions

Restore (undrop) many cancelled OmniFocus tasks in a single JXA round trip. Undropped tasks are returned to active status and will reappear in active task lists. Use task_batch_drop to cancel tasks. Validation is atomic: if any input fails schema, the whole batch is rejected before any mutation. Execution is best-effort: each undrop succeeds or fails independently, and the response reports per-index outcomes. Prefer this tool over repeated task_undrop calls whenever undropping more than one task. Each item is { id }. Returns { undropped: [{index, value: { id, name }}], failed: [{index, errorCode, message}] } — value carries the task name so the agent can describe each restoration without a follow-up read. Side effects: writes to OmniFocus, sets meta.syncPending = true. Call sync_trigger when you need changes to appear on other devices. Example: task_batch_undrop({ items: [{ id: "abc123" }, { id: "abc456" }] })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesArray of { id } items. Must contain at least one item.
idempotency_keyNoIdempotency key for retry-safe batches. Replays within the TTL window return the cached envelope with meta.idempotentReplay = true. See docs/idempotency.md.
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: validation is atomic (rejects whole batch on any schema failure), execution is best-effort (per-index outcomes), side effects (writes to OmniFocus, sets syncPending), idempotency key behavior, and return format with per-index results including task names.

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 and front-loaded with the core purpose. Every sentence adds value, covering purpose, behavior, alternatives, response format, side effects, and an example. There is no redundant information.

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?

Despite lacking an output schema, the description comprehensively explains the return format, side effects, and idempotency. The batch mutation tool has 2 parameters and is fully documented. The description leaves no gaps for an agent to understand its usage.

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 100%, so the baseline is 3. The description adds meaningful context beyond the schema, such as explaining the batch behavior, per-index outcome reporting, and idempotency key usage. It enhances understanding of how the parameters operate in practice.

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 the verb 'restore' and resource 'many cancelled OmniFocus tasks' and distinguishes from sibling tools like task_batch_drop and task_undrop. It explicitly says 'Use task_batch_drop to cancel tasks' and 'Prefer this tool over repeated task_undrop calls whenever undropping more than one task.'

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use this tool (for multiple undrops) and mentions the alternative (task_undrop). It also describes validation atomicity and best-effort execution, which helps the agent understand behavior. However, it does not explicitly state when not to use this tool or list other alternatives beyond undrop.

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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