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tigergraph

tigergraph-mcp

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by tigergraph
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Python
Hybrid

tigergraph__validate_schema_names

Read-onlyIdempotent

Validate vertex, edge, attribute, and graph names against GSQL reserved keywords and naming conflicts before graph creation to catch errors early.

Instructions

Validate vertex type names, edge type names, attribute names, and the graph name against GSQL reserved keywords and naming conflict rules.

Use When:

  • Before calling 'create_graph' to catch naming problems early

  • Checking if user-supplied names conflict with GSQL keywords

  • Validating that vertex/edge type names don't collide with their attribute names

Quick Start:

{
  "graph_name": "MyGraph",
  "vertex_types": [
    {"name": "SELECT", "attributes": [{"name": "count", "type": "INT"}]}
  ]
}

(Returns warnings for 'SELECT' and 'count' as reserved keywords)

Related Tools: create_graph, get_graph_schema

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
edge_typesNoEdge type definitions to validate (same format as create_graph).
graph_nameNoGraph name to validate.
vertex_typesNoVertex type definitions to validate (same format as create_graph).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so no contradiction. The description adds that it returns warnings (via example) and focuses on validation without side effects, which complements the annotations well.

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 well-structured with a main statement, Use When, Quick Start, and Related Tools. It is front-loaded, every section earns its place, and the example is compact and illustrative.

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

Completeness5/5

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

For a read-only validation tool with optional parameters, all input semantics are covered by schema plus description. It explains when to use it, how to format inputs, and what to expect (warnings). No missing critical info for correct invocation.

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 coverage is 100% with descriptions for all three parameters. The description adds a Quick Start JSON example and notes that vertex_types/edge_types follow the same format as create_graph, giving agents concrete usage guidance beyond schema field names.

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 a specific verb ('Validate'), a precise resource (vertex/edge/attribute names and graph name), and the rule set (GSQL reserved keywords and naming conflicts). It is immediately distinguishable from the sibling create_graph and get_graph_schema tools.

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?

The 'Use When' section lists concrete scenarios (before create_graph, keyword conflict checks, attribute-name collisions). It could explicitly state when not to use it, but the context is clear enough to route an agent correctly.

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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