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set_cell_autorefresh

Set a per-cell auto-refresh interval, adaptive polling, or clear the override so a notebook cell inherits the default. Charts and grids only; DDL/DML cells never poll.

Instructions

Set auto-refresh polling for a cell, as a per-cell override of the notebook default (set_notebook_autorefresh). Applies to both chart (draw-mode) and grid (run-mode) cells. A cell containing DDL/DML never polls: the value is stored, but the engine blocks its ticks and read tools report auto_refresh_blocked: "contains_write". Markdown cells are rejected. Nothing polls without a per-cell value or a notebook default. value: true = adaptive poll (interval auto-tuned to response time), false = no polling, a fixed interval string (digits plus ms, s or m, from 50ms to 60m, e.g. "250ms", "5s", "15m"), or null to clear the override so the cell inherits the notebook default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
cell_idYes
buffer_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • changedInput schema / properties / value / anyOf
      Previous value: -[
-  {
-    "type": [
-      "boolean",
-      "null"
-    ]
-  },
-  {
-    "enum": [
-      "1s",
-      "5s",
-      "10s",
-      "30s",
-      "1m"
-    ],
-    "type": "string"
-  }
-]New value: +[
+  {
+    "type": [
+      "boolean",
+      "null"
+    ]
+  },
+  {
+    "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. Changed1 schema field changedv0.3.1
    • changedInput schema / properties / value / anyOf
      Previous value: -[
-  {
-    "type": "boolean"
-  },
-  {
-    "enum": [
-      "1s",
-      "5s",
-      "10s",
-      "30s",
-      "1m"
-    ],
-    "type": "string"
-  }
-]New value: +[
+  {
+    "type": [
+      "boolean",
+      "null"
+    ]
+  },
+  {
+    "enum": [
+      "1s",
+      "5s",
+      "10s",
+      "30s",
+      "1m"
+    ],
+    "type": "string"
+  }
+]
  3. First observedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: DDL/DML cells store the value but the engine blocks ticks, read tools surface auto_refresh_blocked: "contains_write", markdown cells are rejected, and no polling happens without a value or default. This is exactly the kind of non-obvious system behavior an agent cannot infer from the schema.

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?

Every sentence carries load and the scoping statement is front-loaded before the value semantics. It is a single dense block, though, and could be broken into shorter units for easier scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description covers behavior, rejection cases, blocking semantics, and inheritance rules — everything needed to invoke it correctly. Little is left to inference.

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 coverage is effectively low (only the value property carries a description), yet the description fully explains value: true = adaptive poll, false = off, fixed interval string with range 50ms–60m and examples, null = clear the override and inherit the notebook default. buffer_id and cell_id remain undocumented, but their meaning is self-evident.

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 and resource (set auto-refresh polling for a cell) and immediately positions it as a per-cell override of set_notebook_autorefresh, a named sibling. An agent can distinguish it from set_notebook_autorefresh 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 frames this as the per-cell counterpart to set_notebook_autorefresh, states it applies to both chart and grid cells, that markdown cells are rejected, and that nothing polls without a per-cell value or notebook default. When-to-use and when-not conditions are all present.

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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