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ivossos

FCCS MCP Agentic Server

by ivossos

copy_data

Copy financial data between scenarios, years, or periods in Oracle EPM Cloud FCCS to transfer or replicate consolidation information.

Instructions

Copy data between scenarios, years, or periods / Copiar dados

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_scenarioNoSource scenario
to_scenarioNoTarget scenario
from_yearNoSource year
to_yearNoTarget year
from_periodNoSource period
to_periodNoTarget period

Implementation Reference

  • The main asynchronous handler function for the 'copy_data' tool. It builds parameters from inputs and delegates to the FCCS client to submit a copy data job.
    async def copy_data(
        from_scenario: Optional[str] = None,
        to_scenario: Optional[str] = None,
        from_year: Optional[str] = None,
        to_year: Optional[str] = None,
        from_period: Optional[str] = None,
        to_period: Optional[str] = None
    ) -> dict[str, Any]:
        """Copy data between scenarios, years, or periods / Copiar dados entre cenarios.
    
        Args:
            from_scenario: Source scenario.
            to_scenario: Target scenario.
            from_year: Source year.
            to_year: Target year.
            from_period: Source period.
            to_period: Target period.
    
        Returns:
            dict: Job submission result.
        """
        parameters = {}
        if from_scenario:
            parameters["fromScenario"] = from_scenario
        if to_scenario:
            parameters["toScenario"] = to_scenario
        if from_year:
            parameters["fromYear"] = from_year
        if to_year:
            parameters["toYear"] = to_year
        if from_period:
            parameters["fromPeriod"] = from_period
        if to_period:
            parameters["toPeriod"] = to_period
    
        result = await _client.copy_data(_app_name, parameters)
        return {"status": "success", "data": result}
  • The JSON schema definition for the 'copy_data' tool inputs, defining optional string parameters for source and target scenario, year, and period.
    {
        "name": "copy_data",
        "description": "Copy data between scenarios, years, or periods / Copiar dados",
        "inputSchema": {
            "type": "object",
            "properties": {
                "from_scenario": {"type": "string", "description": "Source scenario"},
                "to_scenario": {"type": "string", "description": "Target scenario"},
                "from_year": {"type": "string", "description": "Source year"},
                "to_year": {"type": "string", "description": "Target year"},
                "from_period": {"type": "string", "description": "Source period"},
                "to_period": {"type": "string", "description": "Target period"},
            },
        },
    },
  • Registration of the 'copy_data' tool handler in the central TOOL_HANDLERS dictionary, mapping the tool name to its implementation.
    "copy_data": data.copy_data,
  • Underlying client method that performs the actual HTTP POST request to FCCS for copying data, used by the tool handler.
    async def copy_data(
        self,
        app_name: str,
        parameters: dict[str, Any]
    ) -> dict[str, Any]:
        """Copy data / Copiar dados."""
        if self.config.fccs_mock_mode:
            return {"jobId": "401", "status": "Submitted", "jobType": "CopyData"}
    
        payload = {"jobType": "COPYDATA", **parameters}
        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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions copying data but does not specify if this is a read-only operation, requires permissions, has side effects like overwriting data, or involves rate limits. This leaves critical behavioral traits undefined for a mutation tool.

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 with two language versions, but the English part is front-loaded and efficient. However, the Spanish translation adds redundancy without new information, slightly reducing conciseness. It could be more structured by omitting the translation.

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 of a data copying tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavioral aspects, error handling, or return values, making it incomplete for safe and effective use by an AI agent.

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?

The input schema has 100% description coverage, clearly documenting all 6 parameters. The description adds minimal value by implying the parameters relate to source and target contexts but does not provide additional syntax, format details, or constraints beyond the schema. This meets the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the action ('Copy data') and the domains involved ('between scenarios, years, or periods'), which is specific and informative. However, it does not explicitly differentiate from sibling tools like 'import_journals' or 'import_supplementation_data', which might also involve data movement, so it misses full distinction.

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?

The description provides no guidance on when to use this tool versus alternatives, such as when copying data is preferred over importing or exporting. It lacks context on prerequisites, exclusions, or comparisons to siblings like 'import_journals' or 'export_data_slice'.

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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