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Meridian

by ai.the-meridian
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List Automations

automations_list
Read-only

Lists an app's automations: automation_id, scoped_id, name, status, nodes (node count), description, and timestamps. Does not include the graph — use automation_get for that. Takes the app_id returned by apps_list.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "app_id": "<app_id>"
    },
    "name": "automations_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
app_idYesThe app uuid returned by `apps_list`.
organization_idNoAn organisation uuid or slug. When supplied, `app_id` is resolved within that organisation and may be a slug instead of a uuid, mirroring the Meridian web app.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description's job is to add context – which it does by disclosing the returned field set and the important negative ('does not include the graph'). It does not mention pagination, ordering, or result-size behavior, which is the remaining behavioral gap.

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

Conciseness4/5

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

Three short sentences, front-loaded with the operation and its field list, followed by the exclusion and the prerequisite. The field enumeration earns its place because there is no output schema, and there is no filler wording.

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 no output schema, the description compensates by listing what is returned and what is deliberately omitted, which is exactly what an agent needs for a read tool with 100% schema coverage. Only pagination/volume behavior remains unaddressed, a minor gap for a simple listing operation.

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%, so both `app_id` and `organization_id` are already documented, including the org-scoped slug resolution. The description only repeats the `app_id` provenance from `apps_list` and says nothing about `organization_id`, so it adds little beyond the schema – baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Lists an app's automations') and immediately enumerates the returned fields, so the agent knows the exact shape of the result. It also explicitly distinguishes itself from `automation_get` by stating the graph is not included.

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

Usage Guidelines4/5

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

It names the alternative for graph data ('use `automation_get` for that') and tells the agent where the required `app_id` comes from (`apps_list`), which is clear routing guidance. It stops short of stating exclusions such as pagination limits or when a filtered listing should be preferred.

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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