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VeritasGraph

VeritasGraph

by bibinprathap
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

veritasgraph_structured_ask

Answers questions against connected databases by generating one validated, read-only, row-capped SQL query and returning the SQL, rows, and receipt; refuses when catalog coverage is missing.

Instructions

Answer a question from connected databases with one validated, read-only, row-capped SQL query. Returns the SQL, rows and a receipt; refuses with status no_coverage when the catalog does not cover the question.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "question": "<question>"
    },
    "name": "veritasgraph_structured_ask"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNogoverned: only answer when certified glossary terms cover the question, and withhold answers whose citations are not in the retrieved evidence.
questionYes
connection_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses read-only execution, validation, row capping, one-query scope, return contents (SQL, rows, receipt), and the no_coverage refusal condition. It stops short of covering permissions, error modes beyond no_coverage, or whether the row cap is configurable.

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 two tight clauses, front-loads the core action, and adds useful behavioral details without waste. Every sentence earns its place.

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 tool with no annotations, no output schema, and low schema coverage, the description covers purpose, read-only behavior, return values, and refusal. However, it omits parameter-level meaning for mode and connection_id, so an agent must rely on the schema for key invocation details.

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

Parameters2/5

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

Schema description coverage is only 33%, and the description does not explain the parameters. The question parameter is implied by 'Answer a question,' and connection_id is loosely implied by 'connected databases,' but the mode parameter is left entirely to the schema, leaving a meaningful gap.

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 states a specific verb and resource: answering a question from connected databases via one validated, read-only, row-capped SQL query. It is clear what the tool does, but it does not explicitly distinguish itself from siblings such as veritasgraph_query or veritasgraph_check_answerable.

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?

Usage is implied: use this to answer questions over connected databases when the catalog covers them, because it refuses with no_coverage otherwise. However, there is no explicit when-to-use guidance versus alternatives or prerequisites for choosing this over sibling query/check tools.

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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