ably_list_queuesList the Ably Queues (AMQP/STOMP message queues) provisioned for an app, with their state and messaging stats. Control API: GET /apps/{app_id}/queues.
| Name | Required | Description | Default |
|---|---|---|---|
| app_id | Yes | App id (from ably_list_apps). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description only needs to add context. It adds the exact REST verb (GET), the control-API nature, and the return content ('state and messaging stats'). This is useful context and does not contradict the annotations.
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 sentences, front-loaded with the verb and resource. The parenthetical 'AMQP/STOMP message queues' clarifies the resource type without bloat, and the endpoint line is compact and useful.
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 one-parameter read-only listing tool with a rich schema, the description is nearly complete: endpoint, scope, and response content are mentioned. It does not specify pagination or detailed response structure, but those are not critical for invocation.
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 description coverage is 100%, and the app_id parameter is well described as coming from ably_list_apps. The tool description adds no parameter-level detail, so a baseline score of 3 is appropriate.
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?
Clearly states the operation ('List'), the resource ('Ably Queues (AMQP/STOMP message queues)'), and the scope ('provisioned for an app'). This differentiates it from sibling tools like ably_list_channels and ably_list_namespaces without requiring an agent to open them.
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 gives clear scope ('provisioned for an app') but offers no explicit when-to-use guidance or mention of alternatives. An agent must infer that this is the tool to use for queue listing; there are no exclusion rules or sibling comparisons.
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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Every tool targets a distinct resource and action: account-level stats, app-level stats, channel details, history, presence, presence history, service time, and each control-plane listing (apps, keys, namespaces, queues, rules) are clearly separated. The only potentially confusing pair is account stats vs app stats, but their descriptions explicitly differentiate account-wide vs API-key-scoped usage.
All tools use a uniform 'ably_' prefix followed by a consistent verb_noun pattern: get_ for single resources, list_ for collections, publish_message for the write action, and whoami for token details. There are no mixed casing styles or inconsistent verb choices.
Fifteen tools is within the ideal range and each one covers a meaningful Ably capability, from control-plane inspection to channel data retrieval and publishing. The count feels justified given the breadth of Ably's API surface, with no redundant or filler tools.
The read side is well covered: stats, channel details, history, presence, and control-plane listings all have dedicated tools, and message publishing provides one write path. However, there are no create/update/delete operations for apps, keys, namespaces, queues, or rules, so lifecycle management is largely absent and an agent could not perform common administrative workflows.