GenFlick

Read an automation

native.read_automation

DestructiveIdempotent

One automation in full: its definition, allowance, recent runs with their outcomes and spend, the next run times, and whether it still needs the owner's approval.

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": {
      "work_id": "<work_id>",
      "arguments": "<arguments>",
      "expected_catalog_version": "<expected_catalog_version>",
      "read_skills": "<read_skills>",
      "request_key": "<request_key>"
    },
    "name": "native.read_automation"
  }
}

Input Schema

Name	Required	Description
`work_id`	Yes
`arguments`	Yes
`read_skills`	Yes	Exact required native skills and their dependencies, copied from the accepted session bootstrap's skills array. Include only entries in that array. General mcp.* guides and native.{studio}.instructions are guidance, not native skill proofs.
`request_key`	Yes
`publication_proposal_id`	No	For native Social scheduling, the exact server-approved publication proposal. This identifier cannot confer approval by itself.
`expected_catalog_version`	Yes	For a new session, read a studios/{studio}/native/{pack} child toolset and copy invocation.catalog_version from a native tool descriptor. Do not use the top-level library version. For calls in an existing session, use that session proposal's catalog_version.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 5, 2026

TDQS

C2.8/5.0

Behavior1/5

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

The description frames this as a pure inspection ('One automation in full'), but the annotations declare readOnlyHint=false and destructiveHint=true with openWorldHint=true. An agent reading the prose would treat it as a safe read while the structured metadata warns of a state-changing, destructive operation, and the description gives no explanation of what is mutated, what approval it requires, or why it is not read-only.

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?

A single front-loaded sentence with zero filler, listing the returned facets in a readable order. It is slightly redundant with the output schema, since much of the sentence enumerates return contents rather than guiding the call, but it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values do not need explaining, yet the description spends its one sentence there while ignoring the non-trivial invocation plumbing (catalog version, skill proofs, request key) and the destructive annotation conflict. For a 6-parameter, nested, required-heavy tool that is only partially complete.

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 about 50%: automation_id, read_skills, publication_proposal_id and expected_catalog_version carry field-level prose, but the required work_id, request_key and the arguments wrapper are undocumented. The description adds nothing about any parameter, so it neither compensates for the gap nor misleads — baseline territory.

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 names the resource precisely ('One automation in full') and enumerates its contents — definition, allowance, recent runs with outcomes and spend, next run times, approval state — so it is clearly the single-item reader versus the sibling native.list_automations. It stops short of naming that sibling or using an explicit verb, but the intent is unmistakable.

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 or when-not-to-use guidance. Nothing tells the agent to call native.list_automations first to obtain the automation id (that hint lives only in the nested schema field), nor when to prefer this over native.read_work or native.get_run_status. Usage is only implied by the name.

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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