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Ably MCP by usefulapi

List an app's integration rules

ably_list_rules
Read-only

List the integration rules (reactor rules: webhooks, AWS Lambda/SQS/Kinesis, Kafka, Pulsar, etc.) configured for an app. Control API: GET /apps/{app_id}/rules.

Input Schema

NameRequiredDescriptionDefault
app_idYesApp id (from ably_list_apps).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read. The description adds modest context: it is a Control API operation scoped to a single app. It says nothing about pagination, result limits, or what happens on an invalid app_id, so it clears the lowered annotation-aware bar only modestly.

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

Conciseness5/5

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

Two sentences, zero waste. The core purpose and its disambiguating detail are front-loaded, and the API path is appended rather than padding the opening.

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?

With one required parameter, no annotations beyond readOnly, and no output schema, the description is nearly sufficient: the enumeration of rule types gives the agent a sense of what comes back. It would be complete with a note on result volume or pagination.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the single app_id parameter is already documented in the schema with the same cross-reference ('from ably_list_apps'). The description adds no parameter syntax or format detail beyond the schema, so baseline 3 applies.

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?

The description states a specific verb and resource ('List the integration rules ... configured for an app') and immediately disambiguates the vague term 'rules' by enumerating what they are (webhooks, AWS Lambda/SQS/Kinesis, Kafka, Pulsar). It does not explicitly contrast itself with sibling list tools like ably_list_namespaces or ably_list_queues, so it falls just short of the top band.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives among the many sibling list/get tools. The Control API path is a technical detail, not usage guidance, so an agent gets no routing help.

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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