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ivossos

FCCS MCP Agentic Server

by ivossos

smart_retrieve

Retrieve financial consolidation data from Oracle EPM Cloud FCCS by specifying account, entity, period, years, scenario, and consolidation dimensions for analysis.

Instructions

Smart data retrieval with automatic 14-dimension handling / Recuperacao inteligente

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountYesThe Account member (e.g., 'FCCS_Net Income')
entityNoThe Entity member (default: 'FCCS_Total Geography')
periodNoThe Period member (default: 'Jan')
yearsNoThe Years member (default: 'FY24')
scenarioNoThe Scenario member (default: 'Actual')
consolidationNoThe Consolidation member (default: 'FCCS_Entity Total'). Valid values: 'FCCS_Entity Input', 'FCCS_Entity Consolidation', 'FCCS_Entity Total', 'FCCS_Proportion', 'FCCS_Elimination', 'FCCS_Contribution'.

Implementation Reference

  • The main handler function for smart_retrieve tool. Builds a 14-dimension grid definition with defaults and exports data slice from Consol cube.
    async def smart_retrieve(
        account: str,
        entity: str = "FCCS_Total Geography",
        period: str = "Jan",
        years: str = "FY24",
        scenario: str = "Actual",
        consolidation: str = "FCCS_Entity Total"
    ) -> dict[str, Any]:
        """Smart data retrieval with automatic 14-dimension handling / Recuperacao inteligente de dados.
    
        Args:
            account: The Account member (e.g., 'FCCS_Net Income').
            entity: The Entity member (default: 'FCCS_Total Geography').
            period: The Period member (default: 'Jan').
            years: The Years member (default: 'FY24').
            scenario: The Scenario member (default: 'Actual').
            consolidation: The Consolidation member (default: 'FCCS_Entity Total').
                Valid values: 'FCCS_Entity Input', 'FCCS_Entity Consolidation', 
                'FCCS_Entity Total', 'FCCS_Proportion', 'FCCS_Elimination', 'FCCS_Contribution'.
    
        Returns:
            dict: The retrieved data for the specified dimensions.
        """
        # Build grid definition with hardcoded defaults for 14 dimensions
        grid_definition = {
            "suppressMissingBlocks": True,
            "pov": {
                "members": [
                    [years], [scenario], ["FCCS_YTD"], [consolidation],
                    ["FCCS_Intercompany Top"], ["FCCS_Total Data Source"],
                    ["FCCS_Mvmts_Total"], [entity], ["Entity Currency"],
                    ["Total Custom 3"], ["Total Region"], ["Total Venturi Entity"],
                    ["Total Custom 4"]
                ]
            },
            "columns": [{"members": [[period]]}],
            "rows": [{"members": [[account]]}]
        }
        result = await _client.export_data_slice(_app_name, "Consol", grid_definition)
        return {"status": "success", "data": result}
  • Input schema definition for the smart_retrieve tool within the TOOL_DEFINITIONS list.
    {
        "name": "smart_retrieve",
        "description": "Smart data retrieval with automatic 14-dimension handling / Recuperacao inteligente",
        "inputSchema": {
            "type": "object",
            "properties": {
                "account": {
                    "type": "string",
                    "description": "The Account member (e.g., 'FCCS_Net Income')",
                },
                "entity": {
                    "type": "string",
                    "description": "The Entity member (default: 'FCCS_Total Geography')",
                },
                "period": {
                    "type": "string",
                    "description": "The Period member (default: 'Jan')",
                },
                "years": {
                    "type": "string",
                    "description": "The Years member (default: 'FY24')",
                },
                "scenario": {
                    "type": "string",
                    "description": "The Scenario member (default: 'Actual')",
                },
                "consolidation": {
                    "type": "string",
                    "description": "The Consolidation member (default: 'FCCS_Entity Total'). Valid values: 'FCCS_Entity Input', 'FCCS_Entity Consolidation', 'FCCS_Entity Total', 'FCCS_Proportion', 'FCCS_Elimination', 'FCCS_Contribution'.",
                },
            },
            "required": ["account"],
        },
  • Registration of the smart_retrieve handler in the TOOL_HANDLERS dictionary.
    "smart_retrieve": data.smart_retrieve,
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description fails to explain what 'smart' retrieval entails, how the 'automatic 14-dimension handling' works, what data is returned, whether this is a read-only operation, potential side effects, performance characteristics, or error conditions. It provides no actionable behavioral information beyond the vague title.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (two phrases) but inefficient. The bilingual format ('Recuperacao inteligente') adds no value for an English-speaking AI agent. The phrase 'automatic 14-dimension handling' is cryptic without explanation. While short, it wastes space on redundant or unclear elements rather than providing useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity implied by 'smart' retrieval and 14-dimension handling, with no annotations and no output schema, the description is severely incomplete. It doesn't explain what makes this retrieval 'smart', what the 14 dimensions are, what data format is returned, or how this differs from simpler retrieval tools. For a potentially complex data retrieval operation, this description leaves critical gaps.

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 all 6 parameters thoroughly with descriptions and default values. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Smart data retrieval with automatic 14-dimension handling / Recuperacao inteligente' is vague and tautological. 'Smart data retrieval' restates the tool name 'smart_retrieve' without specifying what makes it 'smart' or what data it retrieves. The mention of '14-dimension handling' is unclear without context. It doesn't distinguish this tool from sibling tools like 'smart_retrieve_consolidation_breakdown' or 'smart_retrieve_with_movement'.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'smart_retrieve_consolidation_breakdown' or 'smart_retrieve_with_movement', nor does it explain what specific scenarios or data types this tool is designed for. There's no indication of prerequisites, constraints, or typical use cases.

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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