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ruya-grp

fusion-query-mcp

by ruya-grp

fusion_list_tables

Read-onlyIdempotent

Search Oracle Fusion Cloud tables by SQL LIKE pattern and owner, sorted by approximate row count, to identify the real transactional table among similarly named objects.

Instructions

List Fusion tables matching a SQL LIKE pattern, most-populated first.

Runs the registered list_tables report with p_pattern / p_owner as bind values. The report applies no row cap of its own, so limit is applied here after the rows arrive and truncated says honestly whether more came back.

approx_rows comes from all_tables.num_rows, an optimiser statistic that can be stale or NULL -- treat it as a hint about which of several similarly named objects is the real transactional one, never as a count. It is also the quickest way to spot the same-name-different-case pairs this pod carries: the populated one is the real table.

The owner and pattern echoed back are the values that were actually bound, which is not always what you passed: omitting one applies the report's registered default, and the full set is in params_used.

Args: pattern: SQL LIKE pattern, e.g. %INVOICE%. % matches any run of characters. Matching is case-insensitive inside the data model. owner: Schema owner; FUSION for application data. The data model compares it with LIKE, not =, so % searches every schema the service account can see. Omit (null) to bind the report's registered default instead (FUSION in the shipped registry). limit: Maximum rows to return from those the report produced. include_views: Not backed by any report -- see the error it returns. datasource: Legacy composed-SQL fallback only; ignored on the report path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
ownerNoFUSION
patternNo%
datasourceNo
include_viewsNo

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior; the description adds substantial non-obvious details: the report has no intrinsic row cap, `truncated` honestly reveals extra rows, `approx_rows` can be stale/NULL, and echoed `owner`/`pattern` may differ from passed values due to defaults. These disclosures go far beyond the annotations and contradict nothing.

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 opens with a one-sentence summary, then uses tight paragraphs and a bulleted Args section. Every caveat—stale statistics, bound-value echoing, no row cap—is load-bearing for correct use, and there is no filler or tautology.

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?

The description fully equips an agent to select and invoke the tool correctly: result interpretation (`approx_rows`, `truncated`, `params_used`), default-binding behavior, and parameter traps are all addressed. Since an output schema already exists, not restating the full return shape is appropriate.

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 carries full responsibility, and it delivers. It explains `pattern` with LIKE syntax and case-insensitivity, `owner` with LIKE-vs-= semantics and default binding, `limit` as a post-report cap, `include_views` as unsupported, and `datasource` as a legacy fallback that is ignored on the report path.

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 opening line states a specific verb and resource: 'List Fusion tables matching a SQL LIKE pattern, most-populated first.' This clearly identifies what the tool does and its distinguishing qualifiers, making it easy to separate from sibling list/describe/query tools even without explicit sibling names.

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?

Provides strong operational context: it runs the registered `list_tables` report, applies `limit` after rows arrive, and warns that `approx_rows` is only a stale hint, never a count. It also flags `include_views` as unsupported and `datasource` as legacy-only, but it never explicitly names alternative tools or gives a direct when-to-use vs. when-not-to-use comparison.

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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