Client Engagement Billing Dispatch Script Generator

Role: Senior Billing Systems Integration Architect with fifteen years of experience in professional services financial operations.

Context

• Professional services practice: {{firm_practice_area}}
• Target ERP platform: {{erp_system_name}}
• Billing contract rules: {{billing_rate_structure}}
• Discrepancy trigger level: {{discrepancy_threshold}}
• Designated approver role: {{approval_authority}}
• Target currency denomination: {{currency_code}}

Task

Draft an end-to-end Python tool calling handler script and JSON schema specifications that an agent can execute to ingest timecard logs, identify unbilled leakage, validate variance thresholds, and post adjustment drafts to {{erp_system_name}}.

Method

1. Define OpenAPI-compatible JSON schemas for three distinct tools: timecard log retrieval, partner rate validation against {{billing_rate_structure}}, and billing adjustment submission.
2. Construct the tool execution dispatcher capable of mapping agent function call requests into executable Python handlers.
3. Implement argument validation logic to verify that all financial figures use {{currency_code}} and align with {{firm_practice_area}} standards.
4. Write mathematical comparison routines evaluating recorded consultant hours against {{discrepancy_threshold}}.
5. Embed an approval routing branch requiring confirmation from {{approval_authority}} when rate overrides exceed policy.
6. Add comprehensive error handling for ERP network timeouts, schema mismatches, and malformed entity IDs.
7. Provide dummy test payload invocations displaying function-call routing, execution output, and formatted agent return messages.

Constraints

• The generated script MUST be syntactically valid Python 3.10+ using type hints and docstrings.
• MUST NOT hardcode mock API keys or sensitive production credentials.
• Tool schemas must explicitly mark mandatory arguments with strict type definitions.
• Error handling MUST return clean structured JSON envelopes rather than raw stack traces.

Output format

1. Function Schemas

JSON schemas for fetch_timecards, validate_rates, and post_adjustment.

2. Implementation Script

Fully commented Python module containing the dispatcher, mock ERP client, and validation rules (70-120 lines).

3. Execution Walkthrough

Step-by-step trace showing an example agent tool call, parameter parsing, and return output.

Self-review

• Verify that {{discrepancy_threshold}} and {{currency_code}} are explicitly parsed in the validation routine.
• Ensure all function definitions match OpenAI tool calling conventions.
• Check that exception paths return JSON error objects.