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tables_db_update_polygon_column

Modify a polygon column in an Appwrite database table to adjust requirements, default values, or column keys for geographic data storage.

Instructions

Update a polygon column. Changing the default value will not update already existing rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase ID.
table_idYesTable ID. You can create a new table using the TablesDB service [server integration](https://appwrite.io/docs/references/cloud/server-dart/tablesDB#createTable).
keyYesColumn Key.
requiredYesIs column required?
defaultNoDefault value for column when not provided, three-dimensional array where the outer array holds one or more linear rings, [[[longitude, latitude], …], …], the first ring is the exterior boundary, any additional rings are interior holes, and each ring must start and end with the same coordinate pair. Cannot be set when column is required.
new_keyNoNew Column Key.
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses one important behavioral trait: 'Changing the `default` value will not update already existing rows.' This is valuable context about the mutation's scope. However, it doesn't mention permissions needed, whether the operation is reversible, error conditions, or what happens to the table structure.

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 extremely concise with just two sentences that both earn their place. The first sentence states the core purpose, and the second provides crucial behavioral context about default values. There's zero wasted text.

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 mutation tool with no annotations and no output schema, the description provides minimal but essential behavioral context about default values. However, it lacks information about what the tool returns, error conditions, or broader implications of updating a polygon column in a database table.

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 6 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema descriptions. The baseline of 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?

The description clearly states the action ('Update a polygon column') and specifies the resource type, which distinguishes it from other column update tools for different data types. However, it doesn't explicitly differentiate from other polygon-related tools like 'tables_db_create_polygon_column' beyond the verb difference.

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 use this tool versus alternatives like creating a new column or using other update tools. It mentions a behavioral constraint about default values not affecting existing rows, but this doesn't help with tool selection decisions.

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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