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ruya-grp

fusion-query-mcp

by ruya-grp

fusion_api_describe

Read-onlyIdempotent

Get the writable field list for a REST resource: types, lengths, allowed values, required source, and child collections. Use it to know what to include before submitting a document.

Instructions

The field list for one REST resource -- the script for collecting input.

Returns each settable field with its type, business description, length limit and list-of-values, plus the child collections (lines, attachments) a complete document usually needs.

Read required_fields and required_source before trusting anything else. When required_source says the pod's own message, that list is authoritative. When it says "not probed", the per-field declared_mandatory flags are the only thing available and they are known wrong in BOTH directions on this pod: ExternallyManagedFlag is declared optional and is required; RequisitionHeaderId is declared mandatory and must not be sent at all.

Args: resource: Exact resource name, e.g. purchaseRequisitions. writable_only: Drop fields the caller can never set (generated ids, audit columns). On purchaseRequisitions this is 25 fields rather than 68 -- the other 43 are questions no user can answer. limit: Maximum number of fields returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
resourceYes
writable_onlyNo

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?

The description goes well beyond the read-only/idempotent annotations by explaining exactly what is returned, how `writable_only` changes the field set, and documenting that `declared_mandatory` flags are unreliable in both directions on this pod. This is precisely the kind of non-obvious behavioral caveat an agent needs.

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 compact but information-dense, with the core purpose front-loaded, followed by return-value details, a critical warning, and parameter semantics. Each sentence earns its place; nothing is filler.

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?

Given the output schema exists and annotations cover safety/idempotency, the description covers the essential calling context: how to name the resource, what to expect in the response, and the known data-quality caveats. An agent has enough to invoke this tool correctly and interpret its output.

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 coverage is 0%, but the description fully compensates: `resource` is explained with a concrete example, `writable_only` is defined with real field-count numbers, and `limit` is described as the maximum number of fields returned. Every parameter gets meaningful semantic context beyond its raw schema type.

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 states it returns the settable field list for one REST resource, with a clear verb ('returns') and resource scope. It also mentions child collections and required-field guidance, and its mention of 'REST resource' distinguishes it from sibling describe tools like fusion_soap_describe and fusion_describe_table.

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 strong contextual guidance: 'Read `required_fields` and `required_source` before trusting anything else' and explains when the pod's own message is authoritative versus when flags are unreliable. It does not explicitly name alternatives or say when not to use this tool, but the provided usage context is clear enough for an agent to know it is the input-collection step.

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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