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studio_status

Check the generation status of notebook artifacts and retrieve their URLs. Also supports renaming artifacts and listing artifact types.

Instructions

Check studio content generation status and get URLs, or rename an artifact.

Args: notebook_id: Notebook UUID action: Action to perform: - status (default): List all artifacts with their status and URLs - rename: Rename an artifact (requires artifact_id and new_title) - list_types: List all supported artifact types with their options artifact_id: Required for action="rename" - the artifact UUID to rename new_title: Required for action="rename" - the new title for the artifact

Returns: Dictionary with status and results. For action="status": - status: "success" - artifacts: List of artifacts, each containing: - artifact_id: UUID - title: Artifact title - type: audio, video, report, etc. - status: completed, in_progress, failed - url: URL to view/download (if applicable) - custom_instructions: The custom prompt/focus instructions used to generate the artifact (if any) - source_ids: List of source UUIDs the artifact was generated from - summary: Counts of total, completed, in_progress

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNostatus
new_titleNo
artifact_idNo
notebook_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so the description covers actions and return structures. However, it does not explicitly disclose that rename is a mutation, lacks warnings about side effects, and omits rate limits or permission requirements.

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?

The description is concise with a clear opening sentence, parameter details, and return structure. Every sentence serves a purpose, though it could be more structured (e.g., separate sections for actions).

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?

Given the tool's scope (status and rename) and presence of output schema, the description covers actions, parameters, and return format adequately. Missing error cases or prerequisites but still complete for typical use.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates by explaining each parameter's role, valid values for action (status, rename, list_types), and conditions (artifact_id and new_title required for rename). Adds significant meaning beyond schema.

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 clearly states it checks studio content generation status and renames artifacts, using specific verbs. It distinguishes from sibling tools like studio_create, studio_delete, studio_revise by focusing on status and rename operations.

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?

The description explains actions and their requirements but does not explicitly guide when to use this tool vs alternatives (e.g., research_status for research, studio_create for creation). Users must infer usage from context.

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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