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Create Tracker queue autoaction

tracker_autoactions_create

Create a scheduled autoaction for a queue to apply defined actions to issues matching a filter or query, with cadence set by interval or calendar.

Instructions

Create an autoaction on a queue — actions applied on a schedule to matching issues.

Required: name and actions (e.g. [{"type": "Update", …}]); scope the issues with filter or query and set the cadence via intervalMillis / calendar. CAUTION: autoactions have no delete endpoint — the action persists until its queue is deleted (it can be disabled in the UI).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesTyped request body for ``autoactions.create`` (``POST /queues/{id}/autoactions``). Supply at least one of ``filter`` or ``query`` to select the issues to act on.
queue_idYesQueue key (case-sensitive, e.g. TEST) or numeric queue id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.67.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false), so the bar is lower, and the description adds genuinely new context: the CAUTION that autoactions have no delete endpoint and persist until the queue is deleted. It still omits auth/permission requirements and whether the response returns the created object, keeping it below 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then a compact Required/scope/cadence sentence and a bolded CAUTION. Every sentence earns its place; the slight overlap with the schema's required-fields prose is the only minor redundancy.

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 mutation tool with no output schema and a deeply nested body, the description covers required fields, scoping, cadence, and the critical non-deletable lifecycle caveat. Missing pieces are return-value behavior and permission needs, but the core call-correctly information is present.

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, but the description adds value by naming the required fields (name, actions), giving a concrete action example ([{"type": "Update", …}]), and pairing the scoping (filter/query) and cadence (intervalMillis/calendar) parameters conceptually. This is more than the schema's per-field prose.

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 and resource ('Create an autoaction on a queue') and adds a functional gloss ('actions applied on a schedule to matching issues') that clarifies the concept. It does not name the nearest sibling (tracker_triggers_create) to distinguish the two, so it falls short of the 5 tier.

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?

The description conveys implied usage (scheduled issue actions scoped by filter/query) and the required fields, but offers no explicit when-to-use vs when-not or comparison against trigger/other automation tools. Guidance is present but left to inference.

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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