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rubayatkhan

mcp-research-pipeline

by rubayatkhan

check_artifact_status

Check whether a NotebookLM artifact generation task has finished by providing the notebook ID and task ID, returning the current status.

Instructions

Check the generation status of a NotebookLM artifact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesTask ID returned by generate_artifact.
notebook_idYesID of the notebook.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Without annotations, the description only states the read-only 'check' operation, which is the core behavior. It does not disclose polling semantics, repeated-call safety, or task-not-found behavior; with no annotations, the description could be more explicit, but the low-risk status-check behavior keeps this at a marginal 3.

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?

One short, front-loaded sentence with no filler. It loses a point because the brevity comes at the expense of usage guidance, but as a standalone statement it is appropriately compact.

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?

For a simple two-parameter poll, the schema covers inputs and an output schema exists, so return-format knowledge is not required. However, the absence of any explicit 'poll after generate_artifact' context or mention of how to know an artifact is ready leaves an agent without the typical workflow.

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%: both task_id and notebook_id already have plain descriptions. The tool description adds no parameter-level detail, so it earns the baseline score rather than credit for compensation.

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 pairs a specific verb ('Check') with a specific resource ('generation status of a NotebookLM artifact'), so an agent can infer the tool's function. It does not explicitly contrast with list_artifacts or generate_artifact, but the focus on status is enough to separate it from generation/download operations.

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?

The description provides no guidance on when to call this tool. It never mentions that it should follow generate_artifact or that list_artifacts is an alternative, so the agent must infer polling context from the parameter schema and sibling names.

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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