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ruya-grp

fusion-query-mcp

by ruya-grp

fusion_get_hints

Read-onlyIdempotent

Get curated Oracle Fusion schema hints to avoid silent row-duplication traps from missing language or effective-date filters before trusting joined results.

Instructions

Curated Oracle Fusion schema knowledge: the traps that corrupt results silently.

Read the relevant topic before trusting a joined result. A missing _TL language filter or _F effective-date predicate does not raise an error -- it multiplies the rows, and the report looks like it worked. That guidance now applies to the SQL an administrator writes into a report's data model, which is where every join on this pod lives.

Args: topic: One of the knowledge-base topics (effective_dating, translations, multi_org, lookups, flexfields, aliasing, po, ap, inv, om, gl, suppliers, getting_started). Omit for the whole base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, so the safety profile is fully covered. The description adds useful domain context about silent row multiplication and the SQL scope, but it does not disclose operational details such as return format, errors, or response size. The output schema appears to cover return structure.

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 front-loaded with a one-line purpose and then provides a brief, relevant example of the silent-corruption trap. The args section is compact and complete. The middle paragraph is slightly verbose but every sentence contributes meaningful guidance.

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 a single-optional-parameter, read-only knowledge tool with an output schema, the description is nearly complete: it covers purpose, usage timing, parameter values, and omission behavior. It does not name sibling alternatives or exclusions, but those are not essential for this simple tool.

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

Parameters5/5

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

The input schema only defines a nullable string `topic` with no enum or description, so 0% schema coverage means the description must compensate. It does so excelently by listing all accepted topic values and explicitly stating that omitting the argument returns the whole base. This fully resolves parameter ambiguity.

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 identifies this as a knowledge-retrieval tool for curated Oracle Fusion schema traps, specifically the silent data-corruption risks in joined results. It is clearly distinct from the sibling query, validation, and report tools, but it lacks an explicit verb like 'retrieve' and does not directly contrast itself with a sibling.

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 description gives a concrete use condition: 'Read the relevant topic before trusting a joined result.' It also explains the failure mode that motivates the tool—missing `_TL` or `_F` predicates multiply rows silently. However, it does not explicitly state when not to use the tool or name alternative 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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