ably_whoamiReturn details about the configured control token: the account and user it belongs to and its capabilities. Good first call to confirm control-plane access. Control API: GET /me.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already marks this as safe, and the description adds useful behavioral context by disclosing what the call returns (account, user, capabilities) and the underlying endpoint 'GET /me'. It does not discuss failure modes or auth details, but for a read-only identity probe the description carries adequate weight.
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, each earning its place: the first states what the tool returns, the second gives usage guidance and the endpoint. There is no filler or repetition of the title.
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 zero-parameter read-only tool, the description is complete: it explains the resource, the returned information, when to use it, and the API path. No output schema is present, but the expected return surface is adequately described for an agent to invoke and interpret the call.
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?
The tool has zero parameters and 100% schema description coverage, so the description is not required to document parameters. It adds implicit semantic context ('configured control token') beyond the empty schema, which is appropriate for a no-argument call.
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 uses a specific verb ('Return') and names the exact resource ('details about the configured control token') and the three facets: account, user, and capabilities. This clearly distinguishes it from the sibling tools, none of which target the token/identity itself.
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?
'Good first call to confirm control-plane access' provides a clear usage context, indicating this tool should be used before other control-plane operations to verify credentials. It does not explicitly name alternative tools or exclusion conditions, but the guidance is sufficient for a zero-parameter identity check.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.