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ruya-grp

fusion-query-mcp

by ruya-grp

fusion_describe_table

Read-onlyIdempotent

Describe an Oracle Fusion table's columns, data types, and comments before querying to avoid column-name errors. Automatically resolves case-duplicate object names to return the accurate schema.

Instructions

Describe ONE Fusion object: ordered columns, data types, comments.

Call this before writing any query that names a column. Fusion column names rarely match the UI labels, and a wrong guess costs a full ORA-00904 round trip. Comments are populated on this pod and are genuinely informative.

The dual-object rule. This pod carries objects whose names differ only in letter case -- FUSION.po_headers_all and FUSION.PO_HEADERS_ALL are two distinct objects, and the dictionary lookup is case-insensitive, so a lookup for one returns both. Presenting their union would show a 288-column table as 576 columns with every name duplicated: a wrong answer that looks like a right one. So the rows are grouped by their exact (OWNER, TABLE_NAME) and exactly one group is ever described:

  1. If exactly one group spells its name the way you did (case-sensitive on the object, case-insensitive on the owner, since Oracle object names created with quotes really are case-sensitive), that group wins -- chosen_by: exact_name_match. Your spelling is the only unambiguous signal available.

  2. Otherwise the best-documented group wins -- chosen_by: most_documented: first a group that has a table comment, then the one with the most commented columns, then the most columns, then name order for determinism. On this pod the documented twin is the real transactional object; its namesake has no statistics and no comments. And it is decided from data the report already returned, so no extra round trip is needed.

Whenever more than one object matched, ambiguous is true, alternates lists every object that was NOT described, and the summary leads with it. The ambiguity is never resolved silently: if the choice is wrong, re-call with the exact spelling you meant (table="po_headers_all").

Args: table: Object name, optionally OWNER.OBJECT, e.g. AP_INVOICES_ALL. Case is preserved and used for the tie-break above. owner: Schema owner used when table is unqualified. datasource: Legacy composed-SQL fallback only; ignored on the report path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerNoFUSION
tableYes
datasourceNo

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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive behavior. The description adds substantial behavioral detail beyond annotations: the case-sensitive dual-object rule, chosen_by tie-breaking logic, ambiguous flag, alternates list, no-silent-resolution guarantee, and the datasource fallback behavior. No contradiction with annotations.

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 long, but it is front-loaded with the core purpose and uses clear headers for complex rules. The dual-object rule justifies much of the length, though some narrative explanation could be trimmed without losing essential guidance.

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?

With an output schema present, return values need not be re-explained. The description covers invocation timing, parameter semantics, ambiguity behavior, and re-call guidance, making it functionally complete for an agent to select and invoke the tool correctly.

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?

Schema description coverage is 0%, so the description fully carries parameter meaning. It explains table as 'OWNER.OBJECT' with case preservation, owner as the fallback schema when table is unqualified, and datasource as a legacy ignored path. This goes well beyond the bare schema properties.

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 opens with a specific verb and resource: 'Describe ONE Fusion object: ordered columns, data types, comments.' It clearly distinguishes this from list/search/sibling documentation tools by emphasizing 'ONE' object and precisely naming the output elements.

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?

It gives explicit usage guidance: 'Call this before writing any query that names a column' and explains the concrete cost of guessing wrong. However, it does not explicitly say when to prefer alternative tools like fusion_docs_describe_table or fusion_search_columns, so it stops short of full exclusions.

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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