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maltego_import_csv

Import CSV data to create entities and links on your Maltego graph. Accepts file path or raw text with type, value, optional notes and link_to columns.

Instructions

Build entities (and optional links) on the active graph from CSV.

Accepts a CSV file path or raw CSV text with a 'type,value' header (optional 'notes' and 'link_to' columns). The 'type' column accepts friendly aliases ('Domain', 'Email', 'IP') or full Maltego type ids. Entities are deduplicated; rows with unknown types are skipped and reported.

Args: params (ImportCsvInput): - path (Optional[str]): Path to a CSV file, OR - content (Optional[str]): Raw CSV text.

Returns: str: Counts of entities added/reused, links added, rows skipped, and any per-row warnings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses mutation (builds on active graph), deduplication, and handling of unknown types. Annotations confirm readOnlyHint=false, no contradiction. Missing detail on what happens if no active graph exists, but overall good 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?

Concise, well-structured description: first sentence states purpose, then format, behavior, args, returns. No fluff or redundancy.

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?

Covers input format, dedup, unknown types, and return value. Minor gap: does not explain how 'link_to' column works to create links. Output schema exists, so return description is sufficient.

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?

Input schema already describes path and content parameters with good detail. Description adds context about CSV format (type,value header, optional columns) and dedup behavior, but does not significantly enhance per-parameter meaning beyond 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?

Description clearly states the tool builds entities (and optional links) on the active graph from CSV. This is a specific verb-resource pair and distinguishes from sibling tools like maltego_add_entity (single entity) and maltego_import_graph (graph file).

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?

Describes input format and behavior (dedup, skip unknown types) well, but does not explicitly say when to use this tool over alternatives like maltego_add_entity for single entries or maltego_import_graph for graph files. Implicit usage context is clear.

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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