ably_list_keysList the API keys for an app, including their capabilities (but not the full secret). Control API: GET /apps/{app_id}/keys.
| 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?
With readOnlyHint=true already provided, the description adds meaningful context: keys are listed with capabilities but the full secret is intentionally excluded. It also identifies this as a Control API GET request, giving an agent a clearer sense of the operation's nature and expected request style.
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?
The description is two sentences, front-loaded with the core action, and contains no filler. Every sentence earns its place by adding either the functional scope or the API endpoint context.
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 list operation, the description covers purpose, the endpoint, and an important output limitation. It does not fully describe the response shape, but no output schema exists and the complexity is low, so the provided information is largely sufficient for correct 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 single parameter app_id is already documented as 'App id (from ably_list_apps)'. The description adds no additional parameter-level meaning beyond restating the endpoint path, 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?
The description states a specific verb and resource: 'List the API keys for an app'. It also clarifies the scope by adding 'including their capabilities (but not the full secret)', which distinguishes this from any secret-returning operation. This is clearly differentiated from sibling tools such as ably_list_channels and ably_list_rules.
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 the tool is for retrieving an app's API keys, but it does not explicitly state when to use it over alternatives or when not to use it. The schema adds context by saying app_id comes from ably_list_apps, but the description itself provides only implied usage guidance.
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.