GenFlick

Read generation defaults

native.get_generation_defaults

DestructiveIdempotent

Read fresh effective generation settings and the saved chat LLM default for the current workspace. In Series, omit project_id for Series/new-project defaults, or pass a linked project ID for that project's saved settings. Returns models, quality, resolution, aspect and duration limits. The current conversation can use a different LLM. Never changes settings.

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_defaults"
  }
}

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

B3.2/5.0

Behavior1/5

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

The description asserts 'Never changes settings' and frames the tool as a pure read, while the supplied annotations declare readOnlyHint=false and destructiveHint=true. Those are mutually exclusive safety profiles, so an agent cannot know whether calling this is safe. The otherwise useful note about scope and return contents does not resolve that conflict.

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?

Four sentences, front-loaded with purpose and return contents, then the project scoping rule, then the caveat. Every sentence carries information and there is no filler, though the Series scoping sentence is dense and slightly awkward to parse on first read.

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 enumerating return fields is a bonus rather than a requirement, and the project scoping rule covers the one meaningful argument choice. For a six-parameter, nested-object tool with a contradictory safety profile, the description does not explain what work_id, request_key, or the catalog-version prerequisite mean for the caller, leaving the invocation contract partly opaque.

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 coverage is 50%, and the description does add real meaning for the one nested argument it mentions: omit project_id for Series defaults versus pass a linked project ID. The five required protocol parameters (work_id, arguments, read_skills, request_key, expected_catalog_version) get no explanation here beyond what the schema's own descriptions provide, so it lands at the baseline.

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: reading 'fresh effective generation settings and the saved chat LLM default' for the current workspace, and it enumerates what comes back (models, quality, resolution, aspect, duration limits). The word 'fresh' implies it is not a cached read, which distinguishes it from native.get_generation_models and native.get_model_options, though those siblings are never named explicitly.

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 gives a concrete branching rule for Series: omit project_id for Series/new-project defaults, or pass a linked project ID for that project's saved settings. It also warns that the current conversation may use a different LLM, which is a useful precondition. It stops short of saying when to reach for this tool instead of get_generation_models or get_model_options.

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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