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set_notebook_autorefresh

Set a notebook-wide auto-refresh default for chart and grid cells; per-cell overrides still win unless reset, and cells with writes never poll.

Instructions

Set the notebook-level auto-refresh default for every cell showing a chart or a grid. Cells with no per-cell value inherit it; set_cell_autorefresh sets a per-cell override that wins over it. Cells containing DDL/DML are skipped — auto-refresh never executes a write. Until this is set, nothing polls. value: true = adaptive poll (interval auto-tuned to response time), false = no polling, or a fixed interval string (digits plus ms, s or m, from 50ms to 60m, e.g. "250ms", "5s", "15m"). reset_cell_overrides: true additionally deletes every per-cell override in the same atomic call, so ALL cells follow the new default — the equivalent of the console's "Reset cell overrides" action. Nothing re-runs; false or null leaves per-cell overrides in place and they keep winning over the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
buffer_idYes
reset_cell_overridesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • changedInput schema / properties / value / anyOf
      Previous value: -[
-  {
-    "type": "boolean"
-  },
-  {
-    "enum": [
-      "1s",
-      "5s",
-      "10s",
-      "30s",
-      "1m"
-    ],
-    "type": "string"
-  }
-]New value: +[
+  {
+    "type": "boolean"
+  },
+  {
+    "description": "Fixed interval: digits plus ms, s or m, from 50ms to 60m, e.g. \"250ms\", \"5s\", \"15m\".",
+    "pattern": "^[1-9][0-9]*(ms|s|m)$",
+    "type": "string"
+  }
+]
  2. Addedv0.3.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that DDL/DML cells are skipped, that auto-refresh never executes a write, that the reset is atomic, and that nothing re-runs. It omits authorization/permission requirements and any return or confirmation behavior, which keeps it short of a 5.

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-loads the core purpose, then layers override relationships, exclusions, and parameter semantics. Dense but nearly every clause earns its place; the value/reset explanation is somewhat verbose but justified by the zero schema coverage.

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?

No output schema and no annotations, so the description must stand alone for a 3-required-param mutation tool, and it largely does — covering scope, inheritance, exclusions, and two of three parameters. The unexplained buffer_id is the main remaining gap.

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?

Schema description coverage is essentially 0% (only the interval-string variant hints at format), so the description must compensate. It explains value thoroughly (true=adaptive, false=no polling, or fixed interval with range 50ms–60m and examples) and explains reset_cell_overrides including its atomicity, but leaves buffer_id undocumented and doesn't note that all three are required.

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?

States a specific verb+resource ('Set the notebook-level auto-refresh default') and immediately scopes it to cells showing a chart or a grid. It distinguishes itself from the sibling set_cell_autorefresh by naming it and defining the override relationship, so the agent can tell them apart without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly describes inheritance semantics (cells without a per-cell value inherit this default), the override rule (set_cell_autorefresh wins), the exclusion (DDL/DML cells skipped), the pre-state ('Until this is set, nothing polls'), and the effect of reset_cell_overrides. This is genuine when-to-use and what-happens guidance.

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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