GenFlick

Read generation models

native.get_generation_models

DestructiveIdempotent

List supported image, video, or audio generation models. An exact model ID restricts the list; descriptive queries return the full catalog for semantic selection. Details returns capabilities and constraints. Reports deployment configuration and video plan eligibility separately. No generation or billing changes.

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.get_generation_models"
  }
}

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

B3.4/5.0

Behavior3/5

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

The annotations are conservative (readOnlyHint=false, destructiveHint=true, idempotentHint=true), and the description adds meaningful scope context: it reports deployment configuration and video plan eligibility separately and performs no generation or billing changes. That 'no generation or billing changes' claim sits in mild tension with the destructive/not-read-only hints, though it only rules out two specific side effects rather than claiming the call is a pure read. It says nothing about the required work/session envelope (request_key, expected_catalog_version, read_skills) or any quota or rate behavior.

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?

Five short sentences, front-loaded with the core capability and no filler. Some phrasing is compressed to the point of ambiguity ('Details returns capabilities and constraints' and 'Reports deployment configuration... separately' both require interpretation), but nothing is redundant.

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?

An output schema exists, so return-value explanation is not required, and the description covers the semantically interesting arguments. For a six-parameter tool with five required parameters including a nested read_skills array and a catalog-version token, it never states the prerequisites for a valid call, leaving a real gap for first-use invocation.

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 50%: read_skills, expected_catalog_version, publication_proposal_id, and query are already documented in the schema. The description reinforces query semantics (exact ID vs. descriptive request) and explains what details=true returns, which is genuinely additive, but leaves work_id, request_key, and kind entirely unexplained in both places.

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 opens with a specific verb and resource ('List supported image, video, or audio generation models'), which is materially clearer than the title alone. It does not distinguish itself from nearby catalog-lookup siblings such as native.get_model_options, native.get_generation_defaults, or native.discover_capabilities, so an agent cannot fully rule those out from the text.

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

Usage Guidelines3/5

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

It gives useful conditional behavior: an exact model ID narrows the result while a descriptive query returns the full catalog for semantic selection, and 'details' switches the payload to capabilities and constraints. What is missing is explicit when-to-use/when-not guidance relative to the sibling model-discovery tools, which is where selection risk actually lives.

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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