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ivossos

FCCS MCP Agentic Server

by ivossos

import_supplementation_data

Import supplementation data into FCCS for financial consolidation and close processes. Use this tool to add supplemental financial information to Oracle EPM Cloud FCCS.

Instructions

Import supplementation data / Importar dados de suplementacao

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parametersNoImport parameters (period, year, scenario, etc.)

Implementation Reference

  • The main tool handler function that executes the import by calling the FCCS client.
    async def import_supplementation_data(
        parameters: Optional[dict[str, Any]] = None
    ) -> dict[str, Any]:
        """Import supplementation data / Importar dados de suplementacao.
    
        Args:
            parameters: Import parameters (period, year, scenario, etc.).
    
        Returns:
            dict: Job submission result.
        """
        result = await _client.import_supplementation_data(_app_name, parameters)
        return {"status": "success", "data": result}
  • The JSON schema definition for the tool's input parameters in the TOOL_DEFINITIONS list.
    {
        "name": "import_supplementation_data",
        "description": "Import supplementation data / Importar dados de suplementacao",
        "inputSchema": {
            "type": "object",
            "properties": {
                "parameters": {
                    "type": "object",
                    "description": "Import parameters (period, year, scenario, etc.)",
                },
            },
        },
    },
  • Registration of consolidation tools, including import_supplementation_data, in the TOOL_HANDLERS dictionary.
    "export_consolidation_rulesets": consolidation.export_consolidation_rulesets,
    "import_consolidation_rulesets": consolidation.import_consolidation_rulesets,
    "validate_metadata": consolidation.validate_metadata,
    "generate_intercompany_matching_report": consolidation.generate_intercompany_matching_report,
    "import_supplementation_data": consolidation.import_supplementation_data,
    "deploy_form_template": consolidation.deploy_form_template,
    "generate_consolidation_process_report": consolidation.generate_consolidation_process_report,
  • The FCCSClient method that performs the actual API POST request to submit the import job.
    async def import_supplementation_data(
        self,
        app_name: str,
        parameters: Optional[dict[str, Any]] = None
    ) -> dict[str, Any]:
        """Import supplementation data / Importar dados suplementares."""
        if self.config.fccs_mock_mode:
            return {"jobId": "701", "status": "Submitted", "jobType": "ImportSupplementationData"}
    
        payload = {"jobType": "IMPORTSUPPLEMENTATIONDATA", **(parameters or {})}
        response = await self._client.post(
            f"/{app_name}/jobs{self._get_query_params()}",
            json=payload
        )
        response.raise_for_status()
        return response.json()
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Import' implies a write/mutation operation, but the description doesn't address permissions needed, whether this overwrites existing data, what happens on failure, or any rate limits. This is inadequate for a mutation tool with zero annotation coverage.

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 technically concise but inefficiently structured. The bilingual repetition adds no value and wastes space that could be used for meaningful context. The single phrase doesn't effectively communicate purpose or usage.

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?

For an import/mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'supplementation data' is, what format it expects, what the import does, or what happens after execution. The agent would struggle to use this tool correctly.

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

Parameters4/5

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

With 100% schema description coverage and only one parameter (a nested object), the schema already documents the parameter structure. The description adds no parameter-specific information beyond what the schema provides, but since there's only one parameter and the schema coverage is complete, the baseline is appropriately high.

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

Purpose3/5

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

The description states the tool imports supplementation data, which is a clear verb+resource combination. However, it doesn't distinguish this from sibling import tools like import_consolidation_rulesets or import_journals, nor does it specify what 'supplementation data' means in this context. The bilingual format adds no semantic value.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. With multiple import tools available (import_consolidation_rulesets, import_journals), the description offers no differentiation or context about appropriate use cases for supplementation data import.

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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