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tables_db_update_line_column

Modify a line column's properties in an Appwrite database table, including requirements, default values, or column key, without affecting existing row data.

Instructions

Update a line 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, two-dimensional array of coordinate pairs, [[longitude, latitude], [longitude, latitude], …], listing the vertices of the line in order. 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 the full burden. It discloses a key behavioral trait: 'Changing the `default` value will not update already existing rows,' which is valuable context about mutation effects. However, it lacks other critical details like whether this operation requires specific permissions, is reversible, or has rate limits, leaving gaps for a mutation tool.

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 a single, efficient sentence that front-loads the purpose and includes a crucial behavioral note. There is no wasted text, making it highly concise and well-structured for quick comprehension.

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?

Given the complexity of a mutation tool with 6 parameters and no annotations or output schema, the description is incomplete. It covers a key behavioral aspect but misses other important context like error conditions, response format, or dependencies. It's adequate as a minimum but has clear gaps for effective tool use.

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 parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage examples. This meets the baseline for high schema coverage but doesn't enhance understanding.

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 verb 'Update' and the resource 'a line column', which is specific and distinguishes it from other column types. However, it doesn't explicitly differentiate from sibling tools like 'tables_db_update_point_column' or 'tables_db_update_polygon_column', which have similar purposes but for different column types.

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, such as other column update tools or general table update tools. It mentions a behavioral constraint about default values, but this doesn't help the agent choose between sibling tools or understand prerequisites like permissions.

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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