FMEPM Connect for Oracle EPM

Find members for a business term

find_members

Read-onlyIdempotent

Finds the members of a dimension that match a business term such as revenue, COGS, expenses or headcount, using built-in synonyms (revenue also matches sales and income) and the tenant's own synonyms from the policy. Returns the matching totals (parents) with their first children, then single members, and a ready question that lists them for the user. Use it before export_data_slice whenever the user names a concept rather than an exact member, and ask the user to choose unless exactly one member matches the term.

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": {
      "term": "<term>"
    },
    "name": "find_members"
  }
}

Input Schema

Name	Required	Description
`term`	Yes	The business term as the user said it, e.g. revenue, COGS, operating expenses, headcount
`limit`	No	Totals to return (default 6); single members are capped at 10
`dimension`	No	Dimension to search (default Account)
`connection`	No	Connection id or label from list_connections. Defaults to the user's default connection.
`application`	No	Application name. Defaults to the connection's application.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 30, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), but the description adds real behavioral detail: synonym sources, result ordering (totals/parents with first children, then single members), the bundled follow-up question, and the implicit result cap. It stops short of stating what happens on zero matches or how truncation is signalled, so not a 5.

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?

Front-loaded with purpose and synonyms, then the routing rule and the result shape — each clause carries information. The second sentence is long and packs return ordering plus interaction guidance, which costs a little scannability.

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?

There is no output schema, and the description compensates by describing the return shape (totals with first children, then single members, plus a ready question). It does not cover the empty-result case, which matters for a search tool an agent must decide whether to escalate past.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents term, limit, dimension, connection and application, including defaults and the 10-item single-member cap. The description adds no parameter-level meaning beyond restating the synonym behavior of 'term', which is the baseline 3 case.

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?

States a specific verb and resource ('Finds the members of a dimension that match a business term') and immediately clarifies the mechanism — built-in plus tenant-policy synonyms — with concrete examples. It is clearly separable from list_dimension_members (enumerate) and export_data_slice (extract data) without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit trigger ('use it before export_data_slice whenever the user names a concept rather than an exact member') and an explicit interaction rule ('ask the user to choose unless exactly one member matches'). The alternative tool and the condition selecting it are both named.

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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