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by tigergraph

tigergraph__run_loading_job_with_data

Execute a TigerGraph loading job with inline data by providing job name, file tag, and data string. Load CSV or JSON data directly into the graph.

Instructions

Execute a loading job with inline data string. The data is posted to TigerGraph and loaded according to the specified loading job definition.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eolNoEnd-of-line character. Default is '\n'. Supports '\r\n'.
dataYesThe data string to load (CSV, JSON, etc.). Example: 'user1,Alice\nuser2,Bob'
profileNoConnection profile name. Omit to use the active default profile. Use 'list_connections' to see available profiles.
timeoutNoTimeout in milliseconds. Set to 0 for system-wide timeout.
file_tagYesThe name of file variable in the loading job (DEFINE FILENAME <fileTag>).
job_nameYesThe name of the loading job to run.
separatorNoData value separator. Default is comma. For JSON data, don't specify.
graph_nameNoName of the graph. If not provided, uses default connection.
size_limitNoMaximum size for input data in bytes (default 128MB).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already signal that this is not read-only and not idempotent. The description adds that data is 'posted to TigerGraph and loaded according to the specified loading job definition,' which conveys the write-like load behavior without contradicting annotations. It does not detail side effects like upsert semantics or partial-failure behavior.

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 two short sentences with the core action front-loaded. The second sentence is somewhat redundant but adds the useful framing that data is posted and interpreted by the loading job definition.

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?

For a nine-parameter tool, the description is adequate but thin: it explains the action and relies on the rich schema for parameter details. It does not mention return values or status reporting, though no output schema exists, and it leaves usage differentiation from the file variant implicit.

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 documents all nine parameters. The description adds little beyond naming the inline-data mechanism, which is a minor complement to the `data` parameter and the loading-job context.

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 a specific action: execute a loading job with an inline data string. The inline-data mode distinguishes it from the sibling `run_loading_job_with_file`, though it does not explicitly name that alternative.

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 phrase 'with inline data string' implies this tool is for cases where data is passed directly rather than read from a file. However, it does not explicitly state when to prefer this over `run_loading_job_with_file` or other data-source tools, so guidance is only implicit.

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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