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notebooklm-mcp

by jacob-bd
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Python
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Source List Drive

source_list_drive

Inspect notebook sources and their Google Drive freshness states to identify stale entries and those eligible for a manual Drive sync.

Instructions

List sources with types and Drive freshness status.

Use before source_sync_drive to identify stale sources. Returned Drive sources include can_sync to identify files eligible for a manual Drive sync attempt. An individual sync attempt may still fail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYesNotebook UUID
skip_freshnessNoIf True, skip per-source freshness checks for faster listing

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.11.2
    • addedInput schema / properties / notebook_id / description
      Added value: +"Notebook UUID"
    • addedInput schema / properties / skip_freshness / description
      Added value: +"If True, skip per-source freshness checks for faster listing"
  2. Addedv0.9.1
  3. Removedv0.8.9
  4. Changed2 schema fields changedv0.7.7
    • removedInput schema / properties / notebook_id / description
      Removed value: -"Notebook UUID"
    • addedInput schema / properties / skip_freshness
      Added value: +{
+  "default": false,
+  "type": "boolean"
+}
  5. First observedv0.6.13

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does add real behavioral context: it explains the meaning of the returned can_sync flag and warns that a sync attempt may still fail. It does not cover auth requirements, pagination, or cost of freshness checks beyond the schema's own hint.

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?

Front-loaded with the purpose, then usage, then a caveat — no filler sentences. Slightly fragmented formatting (bare line breaks) but every sentence earns its place.

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?

An output schema exists, so return-value documentation is not required, yet the description still clarifies the key returned field and its caveat. For a two-parameter read tool this is essentially complete; missing pagination/auth notes are minor.

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 both parameters are already documented in the schema; the description adds no parameter syntax or format detail. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

Specific verb+resource ('List sources') with a clear scope qualifier ('with types and Drive freshness status'). It is distinguishable from near-neighbors like source_describe and source_get_content by its enumeration framing, though it never explicitly contrasts them.

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?

Explicitly routes usage: 'Use before source_sync_drive to identify stale sources.' Names the sibling and the condition that selects this tool. No when-not guidance or mention of the skip_freshness trade-off as a usage decision.

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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