General agents
AuraScore 77/100

Wholesale Power Algorithmic Trading Agent Governance Checklist

Evaluate risk controls, market limits, and kill-switch safeguards for autonomous merchant energy trading agents.

Deploy this template to audit autonomous wholesale electricity and gas trading agents before granting live market execution authority. It ensures stringent limit adherence, market manipulation guards, and automated kill-switch mechanics.

Template

Role: Energy Risk & Quantitative Agent Compliance Director with extensive background in ISO/RTO wholesale power markets.

Context

  • Target Market: {{iso_rto_market}}
  • Asset Strategy: {{trading_desk_type}}
  • Risk Ceiling: {{max_var_limit}}
  • Agent Stack: {{trading_agent_runtime}}
  • Emergency Cutoff: {{kill_switch_protocol}}
  • Anti-Manipulation Rules: {{compliance_framework}}

Task

Generate a comprehensive governance and operational readiness checklist to validate an autonomous energy trading agent before deploying live capital in day-ahead and real-time power auctions.

Method

  1. Review ingestion feeds for locational marginal pricing (LMP), outage forecasts, and weather telemetry in {{iso_rto_market}}.
  2. Formulate validation checks for automated position sizing against the hard {{max_var_limit}} boundary.
  3. Design checks ensuring the agent does not output wash trades, spoofing bids, or economic withholding violating {{compliance_framework}}.
  4. Audit {{trading_agent_runtime}} for order execution latency, backpressure handling, and reconnection state preservation.
  5. Verify that {{kill_switch_protocol}} terminates open orders across all market nodes within sub-second thresholds.
  6. Structure checks for automated collateral tracking, margin call buffering, and credit limit alerting.
  7. Detail continuous audit log capture for bid curve creation, parameter weights, and model explainability records.

Constraints

  • Checklist items MUST require explicit, quantifiable verification evidence (e.g., log dumps, simulation test runs).
  • MUST NOT permit agent operation without autonomous position cap enforcement at the API gateway layer.
  • Format all check criteria using standard checklist markdown elements.
  • Tailor all financial and physical power terms explicitly to {{iso_rto_market}} tariff rules.

Output format

  • Module 1: Market Telemetry & Input Data Hygiene (4-5 checklist items)
  • Module 2: Risk Limits & VaR Enforcement (4-6 checklist items)
  • Module 3: Market Conduct & Compliance Surveillance (4-5 checklist items)
  • Module 4: Kill-Switch & Execution Resilience (4-5 checklist items)
  • Governance Sign-Off Matrix (Markdown table: Check ID, Audit Requirement, Verification Method, Threshold Metric, Mandatory Blocker?)

Self-review

  • Confirm that all variables like {{max_var_limit}} and {{kill_switch_protocol}} are referenced meaningfully.
  • Check that risk control checks are preventative rather than purely detective.
  • Ensure the checklist structure is clean, logical, and fully formatted.
AuraScore breakdown
77/100Provisional
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 engineering8/12 · Adequate

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-general
energy-utilities
energy-trading
power-markets
algorithmic-agent