Reorder Subtasks
reorder_subtasksReorder a parent's subtasks. Pass the complete new order, every one once.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ref | Yes | Task id, #N, or title | |
| order | Yes |
reorder_subtasksReorder a parent's subtasks. Pass the complete new order, every one once.
| Name | Required | Description | Default |
|---|---|---|---|
| ref | Yes | Task id, #N, or title | |
| order | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / order / descriptionRemoved value: -"New order: positions (e.g. [3,1,2]) or subtask ids"Input schema / properties / ref / descriptionPrevious value: -"Task ref: id from the list, #N, or title"New value: +"Task id, #N, or title"Input schema / properties / order / items / maxLengthAdded value: +64Input schema / properties / order / maxItemsAdded value: +100Input schema / properties / ref / maxLengthAdded value: +500Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (mutating, idempotent, non-destructive), the description discloses that the order array must be the complete new order and must include every subtask exactly once. This is useful behavioral context about replacement semantics that the annotations alone do not convey.
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?
Two short sentences deliver the core action and the most critical constraint. Every clause earns its place, and the key caveat about completeness is front-loaded in the second sentence.
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?
For a simple reorder operation, the description is largely complete: it names the action, the resource, and the key constraint on the order array. It does not discuss error behavior or what happens if the array is incomplete, but those are minor gaps given the annotations and simple parameter set.
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?
Schema coverage is only 50%, with the 'order' parameter lacking a description. The description compensates by explaining the crucial semantics of 'order': it must be complete and each item appears once. The 'ref' parameter is only documented by the schema, but the schema description for it is adequate.
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 a specific action ('Reorder') applied to a specific resource ('a parent's subtasks'), distinguishing it from sibling tools like get_subtasks or update_tasks. The phrase 'complete new order, every one once' further clarifies the intended operation.
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 when to use the tool: when a user wants to reorder a parent's subtasks. However, it does not explicitly mention alternatives or situations where this tool should not be used, such as when only partially modifying subtask order might be expected.
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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Each tool targets a distinct resource and action: goals, tasks, subtasks, loops, journal, calendar, and stats are cleanly separated. Descriptions include explicit call-order hints (e.g., get_loops before pull_loops) that reduce ambiguity. No two tools appear to do the same thing.
Tool names consistently follow a verb_noun snake_case pattern: create_, get_, update_, delete_, pull_, reorder_, write_. Even non-standard verbs like pull_loops and write_journal fit the same predictable structure, making the API easy to navigate.
Sixteen tools is slightly above the typical well-scoped range, but the coverage justifies it given the multiple domains: goals, tasks, subtasks, loops, journal, calendar, and focus stats. Each tool has a clear purpose, so none feel redundant or padding.
Goals and tasks have full CRUD coverage, and journal read/write plus loop pulling cover important workflows. Minor gaps exist: loops cannot be created, updated, or deleted, and calendar events are read-only, so some agent actions would require workarounds. Overall, the core planning lifecycle is well supported.