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update_row

Update specific cells in a row with optimistic concurrency. A version check prevents silent overwrites; conflicts return version_conflict.

Instructions

Update one row's cells. cells carries ONLY the changed cells.

version is the row's current version and is checked before the write (optimistic concurrency). If the row changed since you read it you get version_conflict rather than a silent overwrite — read the row again and decide whether your change still applies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cellsYes
row_idYes
versionYes
sheet_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully carries the burden of disclosure. It reveals critical behaviors: partial update semantics ('cells carries ONLY the changed cells'), optimistic concurrency checking via `version`, and the conflict response ('version_conflict rather than a silent overwrite'). This is exemplary transparency.

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 compact and front-loaded with the primary action. The second sentence about cells is essential and the paragraph about version/conflict is valuable guidance. Every sentence earns its place without fluff or repetition.

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?

Despite having no annotations, the description covers the key aspects needed to use the tool safely: single-row scope, partial update, conflict detection, and follow-up action. An output schema exists, so return values don't need elaboration. The tool is well-described for its complexity.

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 0%, so the description must compensate. It adds meaning to the two non-trivial parameters: `cells` (only changed cells, not the whole row) and `version` (current row version used for optimistic concurrency). `sheet_id` and `row_id` are left to be inferred from names/context, which is acceptable. Given the partial compensation, a score of 4 is warranted.

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?

The description opens with a specific verb and resource: 'Update one row's cells.' It clearly states the scope (one row) and distinguishes from the sibling tool 'update_rows' (bulk update) and 'delete_row'. This is a precise, non-tautological purpose.

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?

The description provides clear behavioral guidance: how to use the `version` parameter and what to do when a version conflict occurs ('read the row again and decide whether your change still applies'). It doesn't explicitly name alternatives or exclusion criteria, but the single-row scope is clear and the conflict-handling instructions are actionable.

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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