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VeritasGraph

VeritasGraph

by bibinprathap
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

veritasgraph_structured_search

Search structured-data catalogs by meaning and name to find terms, measures, datasets, and fields without running SQL.

Instructions

Search the structured-data catalog (terms, measures, tables, columns) by meaning and name. No SQL is run.

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": {
      "query": "<query>"
    },
    "name": "veritasgraph_structured_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
kNoMax results (default 10, max 50).
kindsNo
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations supplied, the description must carry the behavioral load. It does disclose two useful traits — retrieval is semantic/keyword by "meaning and name," and no SQL is executed (i.e., a safe metadata read) — but it says nothing about relevance ranking, result shape, permissions, or how matching is scored.

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?

Two short sentences, front-loaded with the purpose and immediately followed by the key non-behavioral constraint. Nothing is wasted or buried.

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

Completeness2/5

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

There is no output schema and no annotations, so the description needs to say more about what comes back and how to narrow results. Two of three parameters are undocumented in both the schema and the description, and the agent is given no sense of whether results are ranked, paginated, or shaped per kind.

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 coverage is only 33%: only `k` carries a description, while `query` and `kinds` are bare (the enum values for `kinds` are listed but uninterpreted). The description compensates for none of this — it never explains that `query` is the natural-language search string or what restricting `kinds` does to results.

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?

Names a specific verb+resource ("Search the structured-data catalog") and enumerates the object types searched (terms, measures, tables, columns), which is concrete enough to picture. It also implicitly separates itself from the SQL-executing query sibling via "No SQL is run," though it never names that sibling the way a top-scoring definition would.

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 usage guidance is implied rather than stated: the agent can infer this is for discovery-style lookups ("by meaning and name") and not for running SQL. However, with siblings like search_terms, search_entities, structured_ask, and query present, there is no explicit statement of when to pick this over those alternatives.

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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