Tool & function calling
AuraScore 83/100

Core Banking Function Calling Schema Design Brief

Design structured function-calling interfaces for real-time transaction monitoring and automated fraud investigation workflows.

Use this template when architecting reliable tool schemas for LLM agents integrated with core banking engines. It guides the definition of deterministic JSON schemas, error boundaries, and banking compliance protocols.

Template

Role: Senior FinTech Systems Architect specializing in deterministic tool integration and core banking systems.

Context

  • Financial Institution: {{institution_name}}
  • Core Banking Platform: {{core_banking_engine}}
  • Monitored Transaction Types: {{transaction_types}}
  • Regulatory and Compliance Baseline: {{compliance_standard}}
  • Target System Latency: {{tool_call_latency_target}}
  • Failure Strategy: {{error_handling_protocol}}

Task

Produce an implementation brief that specifies the tool-calling schemas, parameter validation rules, and runtime safeguards for an AI agent querying and mutating records inside {{core_banking_engine}}.

Method

  1. Analyze the operational parameters of {{transaction_types}} to identify all read and write functions required by the agent.
  2. Draft strict JSON schemas for each tool, explicitly defining required fields, data types, and enum restrictions to satisfy {{compliance_standard}}.
  3. Establish state-verification methods to confirm that pre-call states align before any write function executes in {{core_banking_engine}}.
  4. Define argument validation layers to catch out-of-bounds inputs prior to dispatching network calls.
  5. Design fallback logic and automated retry caps aligned with {{error_handling_protocol}}.
  6. Specify telemetry collection checkpoints to measure tool selection accuracy against {{tool_call_latency_target}}.
  7. Detail manual intervention triggers when schema validation fails consecutively.

Constraints

  • MUST enforce strict typing with zero tolerance for generic object payloads.
  • MUST NOT permit destructive write operations without an explicit two-step confirmation payload.
  • All schema examples must include input validation regex patterns for financial identifiers.
  • Performance overhead per tool evaluation must respect {{tool_call_latency_target}}.

Output format

1. Architectural Overview

Brief description of the agent-to-core integration pattern (maximum 150 words).

2. Tool Schema Specifications

Complete JSON Schema definitions for 3 core banking tools (read, analyze, execute) with inline property descriptions.

3. Execution & Safety Protocol

Step-by-step runtime flow covering parameter validation, error interception, and fallback behavior.

4. Audit & Compliance Log Schema

Structured data contract detailing fields required for audit trails under {{compliance_standard}}.

Self-review

  • Confirm all 6 context variables are directly referenced in the generated specification.
  • Verify that every JSON schema defines required fields and disallows additional properties.
  • Check that the two-step confirmation pattern is explicitly detailed for all write operations.
AuraScore breakdown
83/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

ai-agents
agents-tool-calling
financial-services
function-calling
banking
fintech