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import_graph

Import JSON graph data to merge or replace nodes, edges, and findings in the live visualization workspace.

Instructions

인라인 JSON 데이터를 임포트한다 ([5-E]). payload 1MB 상한.

merge=True 는 identity((id) / (source,target,relation,key))로 멱등 병합, merge=False 는 전체 그래프 교체. 임포트 데이터는 WRITE 검증 경로를 통과하므로 예약('_') 키를 위조할 수 없다([11]/[23-B]) — 서버관리 필드는 무시된다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes{nodes, edges, findings} JSON (문자열 또는 객체).
mergeNo
formatNojson

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A4.3/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does well: 1MB payload limit, idempotent merge vs full replacement, WRITE validation path, and reserved-key/server-managed-field behavior are all disclosed. This goes well beyond the input schema.

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 definition is compact and front-loaded, starting with purpose and constraint, then merge behavior, then validation/security. The bracketed spec references add some noise but do not seriously undermine readability.

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?

For an import tool with an output schema and no annotations, the description is nearly complete: input structure, size limit, merge behavior, and validation consequences are covered. Minor omissions are format semantics and explicit error behavior on oversize payloads.

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

Parameters4/5

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

Schema description coverage is only 33%, so the description must compensate for undocumented parameters. It explains the data shape, the 1MB constraint, and the exact semantics of merge=True/False. The format parameter is not explained, though its name and default 'json' make the omission low-risk.

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 states a specific verb and resource: '인라인 JSON 데이터를 임포트한다' (imports inline JSON data). The 'inline' qualifier distinguishes it from the sibling import_from_file, and the merge/replace behavior further clarifies what the tool does.

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?

It gives clear conditional guidance for merge=True vs merge=False, which is useful for parameter choice. However, it never explicitly names alternatives such as import_from_file or push_batch, nor states when to prefer one over the other. The 'inline' qualifier implies the boundary but no exclusions are spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.