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tigergraph__run_installed_query

Destructive

Run a pre-installed GSQL query on TigerGraph with parameters for fast, repeated execution. Ideal for performance-critical operations after installing the query once.

Instructions

Run an installed GSQL query on a TigerGraph graph with parameters. Faster than interpreted queries for repeated execution.

Use When: • Running pre-installed, compiled queries • Queries that are executed frequently • Performance-critical operations • Parameterized queries with different inputs

Quick Start:

{
  "query_name": "getPersonFriends",
  "params": {"personId": "user123", "maxHops": 2}
}

Common Workflow:

  1. Install query once with 'install_query'

  2. Run multiple times with 'run_installed_query' and different params

  3. Much faster than 'run_query' for repeated use

Tips: • Queries must be installed first with 'install_query' • Use 'is_query_installed' to check if query exists • Provide params as dictionary matching query signature • Faster than interpreted queries

Related Tools: install_query, is_query_installed, show_query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoQuery parameters.
profileNoConnection profile name. Omit to use the active default profile. Use 'list_connections' to see available profiles.
graph_nameNoName of the graph. If not provided, uses default connection.
query_nameYesName of the installed query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already provide destructiveHint true, so the description doesn't need to repeat that. It adds useful context: performance benefits, installation prerequisite, and the workflow of installing once and running multiple times. It doesn't mention side effects, but annotations cover that. No contradiction.

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 sections (Use When, Quick Start, Workflow, Tips), but it repeats the performance claim twice and is somewhat lengthy. Still, every section adds value, and the key purpose is front-loaded.

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?

The description covers when to use, prerequisites, and workflow, but lacks any mention of the return value or response format. Since there is no output schema, the agent has to infer that the tool returns query results. It also doesn't discuss error handling, though that might be less critical. Overall, it's mostly complete but missing the output expectation.

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 descriptions are already detailed for profile and graph_name, but params description is minimal. The description adds clarity by stating 'params as dictionary matching query signature' and provides a concrete JSON example, which helps the agent understand the expected structure.

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 the verb 'Run' and the resource 'installed GSQL query', and distinguishes itself from run_query by emphasizing 'installed' and 'faster than interpreted'. It also lists related tools, making its role clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'Use When' section lists conditions (pre-installed, frequent, performance-critical, parameterized) and contrasts with run_query for repeated use. The workflow explicitly says to install first and use is_query_installed to check.

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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