ably_get_presenceList the members currently present on a channel (who is online now). REST: GET /channels/{channel}/presence.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max members (<=1000). Default 100. | |
| channel | Yes | Channel name. | |
| clientId | No | Filter to a specific clientId. | |
| connectionId | No | Filter to a specific connectionId. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the REST GET endpoint and clarifies current-state semantics, but does not disclose additional behavior such as response shape, default limit, or filtering implications beyond what the schema already states.
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?
A single front-loaded sentence conveys the resource, semantics, and REST endpoint with no filler. Every word contributes to understanding.
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 read-only list operation with one required parameter, the description, annotations, and fully documented schema provide enough to select and call the tool. There is no output schema, but 'List the members' adequately hints at the return; explicit pagination/response details would make it fully complete.
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%, so the baseline of 3 applies. The description mentions the channel in the REST path but adds no deeper meaning beyond the schema's own descriptions for limit, clientId, and connectionId.
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?
Uses a specific verb ('List') and resource ('members currently present on a channel'), with plain-language gloss 'who is online now'. This clearly identifies the tool's purpose and distinguishes it from siblings like ably_get_presence_history or ably_get_channel_details.
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 phrase 'currently present' and 'who is online now' imply real-time presence rather than history, but the description never explicitly says when to use this tool over ably_get_presence_history or other alternatives. No exclusionary guidance is provided.
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.