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FCCS MCP Agentic Server

by ivossos

get_journal_details

Retrieve detailed journal information from Oracle EPM Cloud FCCS by specifying journal label, with options to filter by scenario, year, period, and include line items.

Instructions

Get detailed information about a specific journal / Obter detalhes de um diario

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
journal_labelYesThe journal label
scenarioNoFilter by scenario
yearNoFilter by year
periodNoFilter by period
line_itemsNoInclude line items (default: true)

Implementation Reference

  • The main handler function for the 'get_journal_details' tool. It processes input parameters, constructs optional filters, calls the underlying FCCS client method, and returns formatted results.
    async def get_journal_details(
        journal_label: str,
        scenario: Optional[str] = None,
        year: Optional[str] = None,
        period: Optional[str] = None,
        line_items: bool = True
    ) -> dict[str, Any]:
        """Get detailed information about a specific journal / Obter detalhes de um diario.
    
        Args:
            journal_label: The journal label.
            scenario: Filter by scenario.
            year: Filter by year.
            period: Filter by period.
            line_items: Include line items (default: true).
    
        Returns:
            dict: Journal details.
        """
        filters = {}
        if scenario:
            filters["scenario"] = scenario
        if year:
            filters["year"] = year
        if period:
            filters["period"] = period
    
        details = await _client.get_journal_details(
            _app_name, journal_label, filters if filters else None, line_items
        )
        return {"status": "success", "data": details}
  • The input schema definition for the 'get_journal_details' tool, specifying parameters, types, descriptions, and required fields.
    {
        "name": "get_journal_details",
        "description": "Get detailed information about a specific journal / Obter detalhes de um diario",
        "inputSchema": {
            "type": "object",
            "properties": {
                "journal_label": {"type": "string", "description": "The journal label"},
                "scenario": {"type": "string", "description": "Filter by scenario"},
                "year": {"type": "string", "description": "Filter by year"},
                "period": {"type": "string", "description": "Filter by period"},
                "line_items": {"type": "boolean", "description": "Include line items (default: true)"},
            },
            "required": ["journal_label"],
        },
    },
  • Registration of the 'get_journal_details' handler (along with related journal tools) in the central TOOL_HANDLERS dictionary used by the agent to dispatch tool calls.
    "get_journals": journals.get_journals,
    "get_journal_details": journals.get_journal_details,
    "perform_journal_action": journals.perform_journal_action,
    "update_journal_period": journals.update_journal_period,
    "export_journals": journals.export_journals,
    "import_journals": journals.import_journals,
  • Low-level helper method in the FCCS client that performs the actual HTTP GET request to retrieve journal details from the FCCS REST API.
    async def get_journal_details(
        self,
        app_name: str,
        journal_label: str,
        filters: Optional[dict[str, str]] = None,
        line_items: bool = True
    ) -> dict[str, Any]:
        """Get journal details / Obter detalhes do lancamento."""
        if self.config.fccs_mock_mode:
            return {"journalLabel": journal_label, "lineItems": []}
    
        query_parts = []
        if filters:
            filter_parts = []
            for key in ["scenario", "year", "period"]:
                if key in filters:
                    filter_parts.append(f'"{key}":"{filters[key]}"')
            if filter_parts:
                query_parts.append(f"q={{{','.join(filter_parts)}}}")
    
        query_parts.append(f"lineItems={str(line_items).lower()}")
        query = "?" + "&".join(query_parts)
    
        response = await self._client.get(
            f"/{app_name}/journals/{quote(journal_label)}{query}{self._get_query_params(True)}"
        )
        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 full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are needed, how errors are handled, or the format of returned details. The phrase 'detailed information' is vague and doesn't specify what details are included beyond line items.

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?

The description is brief and front-loaded with the primary purpose. The bilingual repetition ('Obter detalhes de um diario') adds redundancy but doesn't significantly impact clarity. It could be more structured by explicitly mentioning key parameters like 'journal_label'.

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 a tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'detailed information' includes, how filters interact, or the expected output format. Given the complexity and lack of structured support, more context is needed for effective use.

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 fully documents all 5 parameters. The description adds no parameter-specific information beyond implying retrieval of a journal, which is already covered by the tool name and schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 verb ('Get') and resource ('detailed information about a specific journal'), making the purpose evident. It distinguishes from sibling 'get_journals' (plural) by specifying retrieval of details for a single journal. However, it doesn't explicitly differentiate from other retrieval tools like 'smart_retrieve' or 'query_local_metadata'.

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 on when to use this tool versus alternatives. The description doesn't mention prerequisites, context for usage, or compare it to similar tools like 'get_journals' (which likely lists journals) or 'smart_retrieve' (which might retrieve broader data).

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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