Workflow chains
AuraScore 81/100

Pharmacovigilance Multi-Step Agent Orchestration Assessment

Conduct a technical analysis of chained AI agent workflows for adverse event intake, MedDRA triage, and ICSR regulatory generation.

Use this template when designing or auditing an automated multi-step adverse event reporting chain. It systematically analyzes triage accuracy, vocabulary alignment, and regulatory compliance risks across agent handoffs.

Template

Role: Principal Safety Automation Specialist and Pharmacovigilance Regulatory Systems Analyst.

Context

  • Intake Case Ingestion Volume: {{adverse_event_volume}}
  • Source Narrative Modalities: {{source_data_modalities}}
  • Medical Dictionary Standard: {{meddra_coding_standard}}
  • Mandatory Submission Window: {{regulatory_reporting_window}}
  • Auto-Progression Confidence Score: {{confidence_score_cutoff}}
  • Auditability and Data Lineage Standard: {{audit_trail_requirements}}

Task

Deliver a comprehensive technical analysis of the multi-agent pharmacovigilance pipeline, assessing agent coordination during unstructured narrative ingestion, automated MedDRA term mapping, causality assessment, and individual case safety report (ICSR) generation.

Method

  1. Deconstruct the workflow topology into sequential agent tasks: Ingestion, Triage, Entity Extraction, MedDRA Coding, and ICSR Synthesis.
  2. Analyze narrative parsing vulnerabilities across {{source_data_modalities}} to identify entity hallucination risks.
  3. Evaluate semantic alignment routines against {{meddra_coding_standard}} across agent handoffs.
  4. Measure cumulative pipeline processing time to ensure strict adherence to {{regulatory_reporting_window}}.
  5. Audit the routing logic governed by {{confidence_score_cutoff}} to prevent unverified serious adverse events from auto-closing.
  6. Evaluate state tracking and schema validation between upstream extraction agents and downstream XML generation nodes.
  7. Verify that every node-to-node payload transfer satisfies {{audit_trail_requirements}}.

Constraints

  • MUST analyze data loss risks across every serial agent boundary in the pipeline.
  • MUST NOT accept automated causality assignment without verifying safety physician sign-off pathways.
  • All terminology checks must strictly align with {{meddra_coding_standard}}.
  • Recommendations MUST balance the throughput required for {{adverse_event_volume}} with zero-tolerance regulatory penalties.

Output format

  • Architectural Chain Overview (200 words)
  • Step-by-Step Data Handoff and Vulnerability Matrix (Structured table with: Step, Agent Function, Error Vector, Mitigation)
  • Latency and Throughput Feasibility Review (250-300 words)
  • Regulatory Auditability Gap Analysis (200-250 words)
  • Target Topology Recommendations (Numbered action plan with 5 distinct technical steps)

Self-review

  • Have I addressed the specific ingestion risks for all modalities in {{source_data_modalities}}?
  • Is the evaluation aligned with the turnaround time demanded by {{regulatory_reporting_window}}?
  • Did I verify traceability mechanics under {{audit_trail_requirements}}?
AuraScore breakdown
81/100Provisional
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.

Robustness3/5 · Adequate

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-workflows
healthcare-life-sciences
pharmacovigilance
adverse-events
workflow-orchestration