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hungln105-cell

notebooklm-mcp-cli

Research Status

research_status

Poll research progress in NotebookLM, blocking until completion or timeout. Provide notebook ID and optional task ID to wait for results; configurable wait and poll intervals.

Instructions

Poll research progress. Blocks until complete or timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional query text for fallback matching when task_id changes (deep research). Contributed by @saitrogen (PR #15).
compactNoIf True (default), truncate report and limit sources shown to save tokens. Use compact=False to get full details.
task_idNoOptional Task ID to poll for a specific research task.
max_waitNoMax seconds to wait (default: 900, 0=single poll)
auto_importNoIf True, automatically import sources when research completes. If False (default), returns next_action hint to call research_import manually.
notebook_idYesNotebook UUID
poll_intervalNoSeconds between polls (default: 30)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.5

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It does reveal the critical blocking behavior and timeout termination, which is valuable. However, it omits potential side effects such as auto_import behavior or what happens on timeout (e.g., partial results), leaving gaps for a caller to discover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no filler. It front-loads the core action ('Poll research progress') and then states the key behavior. Every word earns its place.

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?

The output schema and complete parameter documentation cover the return shape and inputs, so the description only needs to add behavioral and workflow context. It covers blocking behavior but lacks workflow placement (after research_start, before research_import) and does not distinguish from sibling status tools. This makes it adequate but not 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 100%, so the schema already documents all 7 parameters thoroughly. The description adds no extra parameter-level detail beyond the schema, so the baseline of 3 is appropriate.

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 uses a specific verb ('Poll') and a clear resource ('research progress'), and adds the key behavioral trait that it blocks until completion or timeout. It is distinct from research_start and research_import, though it does not explicitly differentiate itself from similar status tools like notebook_query_status.

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 implies its usage: call this to poll research progress and wait for completion. However, it gives no explicit guidance on when to use it versus alternatives, nor does it mention that it should follow research_start or precede research_import. This is implied usage, not explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.