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Google_sheets

by io.github.pipeworx-io

Sheets Write

sheets_write
Idempotent

Write data to a Google Sheet range, overwriting existing values. Specify sheet name, range (e.g., 'A1:C10'), and row data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesA1 notation range (e.g., "Sheet1!A1")
valuesYesArray of rows, each row is an array of cell values
spreadsheet_idYesSpreadsheet ID
value_input_optionNoHow to interpret input. USER_ENTERED (default) parses formulas/dates/numbers. RAW stores literal strings.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError code if connection required
messageNoError message if connection required
updatedRowsNoNumber of rows updated
updatedCellsNoTotal number of cells updated
updatedRangeNoRange that was updated
spreadsheetIdNoSpreadsheet ID that was written to
updatedColumnsNoNumber of columns updated

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds that it 'overwrites existing values', which is consistent. However, it does not add significant behavioral context beyond what annotations already convey, such as authentication needs or rate limits.

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 concrete range example. Every word earns its place, with no fluff or redundancy.

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?

Given the complete schema with examples and the existence of an output schema, the description sufficiently covers the tool's purpose and basic usage. It explicitly mentions the key parameters (sheet name, range, row data) and the fact that it overwrites, which is the core functionality.

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% with detailed parameter descriptions and examples. The description merely summarizes parameters ('Specify sheet name, range, and row data') without adding new semantic meaning beyond what the schema provides.

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 clearly states the tool writes data to a Google Sheet range and overwrites existing values. It uses a specific verb ('write') and resource ('Google Sheet range'), and distinguishes itself from sibling tools like sheets_append and sheets_read by explicitly mentioning overwriting.

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

Usage Guidelines3/5

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

The description implies when to use this tool (when overwriting values) but does not explicitly contrast with sheets_append for appending rows or provide when-not-to-use guidance. The differentiation is implicit through the word 'overwriting', but no alternative tools are named.

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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TDQS

B3.1/5.0
Disambiguation2/5

Several tools are nearly identical: ask_pipeworx and ask_pipeworx_beta are explicitly the same, and ask_pipeworx, ask_pipeworx_grounded, and deep_research all serve overlapping research/query purposes. discover_tools and suggest_questions both act as discovery entry points, while the five polymarket tools differentiate primarily through intricate details that are easy to confuse.

Naming Consistency2/5

Naming conventions are mixed across the set: verb_noun (ask_pipeworx, resolve_entity, validate_claim), noun_verb (sheets_append, sheets_create), noun_noun (polymarket_arbitrage, entity_profile), and bare verbs (forget, recall, subscribe). The sheets tools are internally consistent but the broader collection has no uniform pattern, with awkward names like pipeworx_trending and search_within.

Tool Count2/5

With 36 tools, the server exceeds the 25-tool threshold for 'too many'. The Google Sheets portion accounts for only 5 tools, while the majority are highly specialized Pipeworx and Polymarket tools that could be consolidated or dramatically reduced. The count feels inflated relative to the advertised 'Google_sheets' server name and its actual core purpose.

Completeness2/5

For a server named Google_sheets, the essential operations exist (create, read, write, append, list structure), but there is no delete/clear range tool and no way to add a new sheet to an existing spreadsheet. For the broader data/research scope, important lifecycles are missing (e.g., no direct way to write Pipeworx results into Sheets, no update for subscriptions, only cancel). The set falls short of fully covering either domain.

Resources