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get_cell_value

Retrieve specific cell values from CSV data using row and column coordinates, returning data with type information for analysis.

Instructions

Get value of specific cell with coordinate targeting.

Supports column name or index targeting. Returns value with coordinates and data type information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
row_indexYesRow index (0-based) to retrieve cell from
columnYesColumn name or column index (0-based) to retrieve

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesCell value (None if null/missing)
successNoWhether operation completed successfully
data_typeYesPandas data type of the column
coordinatesYesCell coordinates with row index and column name
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'Returns value with coordinates and data type information,' which adds some context about output format. However, it lacks critical details such as error handling (e.g., for invalid coordinates), performance implications, or whether it's a read-only operation (implied but not stated).

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 and well-structured: two sentences that efficiently convey core functionality and return information. Every sentence earns its place with no wasted words, and key details are front-loaded.

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

Completeness4/5

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

Given the tool's low complexity (2 parameters, 100% schema coverage, output schema exists), the description is reasonably complete. It covers the basic operation and return format, and with an output schema, it doesn't need to detail return values. However, it could benefit from more behavioral context, especially since no annotations are provided.

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 fully documents the two parameters (row_index and column). The description adds marginal value by noting 'Supports column name or index targeting,' which clarifies the dual nature of the 'column' parameter but doesn't provide additional syntax or format details beyond what the schema specifies.

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 tool's purpose: 'Get value of specific cell with coordinate targeting.' It specifies the verb ('Get'), resource ('value of specific cell'), and targeting method ('coordinate targeting'). However, it doesn't explicitly differentiate from sibling tools like 'get_column_data' or 'get_row_data' that retrieve broader data sets.

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. It doesn't mention sibling tools like 'get_column_data' for column-wide retrieval or 'find_cells_with_value' for value-based searches, nor does it specify prerequisites or exclusions for use.

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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