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import_csv_file

Import messages from CSV, TSV, or delimited files by providing column names for message text, sender, and timestamp. Auto-detects delimiter format.

Instructions

Import messages from any CSV file. Provide column names for your data format.

Auto-detects delimiter (comma, tab, semicolon). Supports header rows. Covers LinkedIn exports, any spreadsheet or custom CSV format.

Args: file_path: Path to the CSV, TSV, or delimited file content_column: Column name containing the message text (required) sender_column: Column name containing the sender name (optional) timestamp_column: Column name containing the timestamp (optional, auto-detects format) source_label: Label to tag imported messages with (default: 'csv-import')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
content_columnYes
sender_columnNo
timestamp_columnNo
source_labelNocsv-import
Behavior3/5

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

No annotations are provided, so the description must carry behavioral disclosure. It mentions auto-detection of delimiter and support for headers, but lacks details on error handling, file size limits, duplicate handling, or side effects. The description provides moderate transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary line, followed by additional details and parameter documentation. It is efficient but slightly verbose in listing example sources. Most sentences add value.

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 5 parameters (2 required) and no output schema, the description covers parameter usage and general behavior. However, it omits details on return values, success/failure indications, and prerequisites. While adequate, it could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The JSON schema has 0% description coverage, but the description's Args section thoroughly explains each parameter, including required ones like content_column and optional like timestamp_column with auto-detection. It adds significant meaning beyond the schema.

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 'Import messages from any CSV file,' specifying the action (import) and resource (messages from CSV). It also lists supported formats and provides examples like LinkedIn exports, differentiating it from sibling import tools for other formats.

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 usage for CSV files and mentions specific sources, but does not explicitly state when to use alternatives (e.g., import_json_file) or provide conditions for not using this tool. Some guidance on exclusion is missing.

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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