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Prompt Details

Model
Chat - (gpt-5.6)
Token size
2,614
Example input
[Agent purpose, role, tasks, success criteria]: Cloud Infrastructure Incident Response Agent Purpose: Autonomously detect, investigate, and mitigate production infrastructure incidents. Primary Task: When a production service becomes unhealthy, determine the likely cause, perform only approved remediation actions, validate recovery, and escalate when autonomous remediation is unsafe or unsuccessful. [Agent steps, decisions, reasoning summaries, state transitions]: Checkout API error rate exceeded 15% for 5 consecutive minutes." Agent Execution Agent receives the production alert. Agent identifies the affected service as checkout-api. Agent queries service health metrics. Metrics show: Error rate: 18.7% CPU utilization: 94% Request latency: 4.8 seconds Agent checks recent deployments. No deployment occurred during the incident window. [Tools used, inputs, outputs, errors, sequence]: Tool 1 β€” Service Metrics Input: Service: checkout-api Time window: last 15 minutes Output: Error rate: 18.7% CPU: 94% Latency: 4.8 seconds Tool 2 β€” Deployment History Input: Service: checkout-api Time window: last 30 minutes Output: No recent deployment. Tool 3 β€” Instance Health Input: Service: checkout-api Output: Instance A: Healthy Instance B: Healthy Instance C: Unhealthy Instance D: Healthy [Agent responses / actions / deliverables]: Checkout API incident resolved. The unhealthy application instance was restarted successfully. Error rate decreased from 18.7% to 7.2% and latency improved from 4.8s to 1.9s." [Quality Score / Audit / Failure Analysis / Improvement Plan]: determine: Whether the diagnosis was correct. Whether the restart was justified. Whether tool selection was appropriate. Whether the agent interpreted post-remediation metrics correctly. Whether the final resolution statement was accurate. Whether escalation was required. What caused the incorrect final state. How the workflow should be improved. Which regression tests should be added.
Example output
1. πŸ“ EXECUTIVE SUMMARY The agent demonstrated good initial incident investigation and reasonable remediation, but it failed at the most important final verification step. The restart was justified because: One application instance was unhealthy. CPU utilization was extremely high. Database health was normal. No recent deployment explained the incident. Restarting the unhealthy instance was explicitly permitted. However, the agent made a critical process error: It treated partial improvement as complete recovery. The final error rate was 7.2%, while the normal threshold was below 2%. Therefore: Remediation succeeded partially. Incident resolution was NOT achieved. --- 2. πŸ”„ EXECUTION RECONSTRUCTION Step Agent Action Evidence Assessment 1 Receives alert Error rate >15% βœ… Correct 2 Identifies service checkout-api βœ… Correct 3 Checks metrics 18.7% errors, 94% CPU βœ… Correct 4 Checks deployments No recent deployment βœ… Appropriate 5 Checks instances Instance C unhealthy βœ… Appropriate 6 Checks database Normal βœ… Appropriate 7 Diagnoses likely cause Unhealthy instance βœ… Reasonable 8 Restarts instance C Restart permitted βœ… Correct 9 Checks recovery metrics Error rate 7.2% βœ… Correct 10 Interprets recovery Declares resolved ❌ Incorrect 11 Sends resolution Claims incident resolved ❌ Incorrect πŸ”΄ Key Failure Point The agent collected the correct post-remediation evidence but interpreted it incorrectly. This is an important distinction: Evidence collection = successful Evidence interpretation = failed --- 3. 🧠 DECISION QUALITY AUDIT Decision 1 β€” Investigate the Alert Status: CORRECT βœ… The agent did not blindly perform a remediation immediately. It gathered service metrics first. --- Decision 2 β€” Investigate Recent Deployments Status: CORRECT βœ… Checking deployments is relevant when investigating sudden production degradation. The result showed no deployment during the incident window. --- Decision 3 β€” Investigate Application Instances Status: CORRECT βœ… The agent found one unhealthy instance among four. This provided meaningful evidence for the remediation decision. --- Decision 4 β€” Check Database Health Status: CORRECT βœ… The database was healthy, reducing support for a database-originated incident. --- Decision 5 β€” Restart Instance C Status: CORRECT βœ… The restart was: Relevant Authorized Targeted Non-destructive Supported by available evidence The agent did not terminate an instance or make an unauthorized database change. --- Decision 6 β€” Declare Incident Resolved Status: INCORRECT ❌ This was the major decision failure. The agent observed: Error rate = 7.2% while the normal threshold was: Error rate <2% Therefore, the service was still degraded. The correct decision should have been: CONTINUE INVESTIGATION / ESCALATE rather than: RESOLVED --- 4. πŸ”§ TOOL-CALL QUALITY AUDIT Tool Selection Status: STRONG βœ… The selected tools were relevant to incident diagnosis and remediation. --- Tool Timing Status: STRONG βœ… The agent investigated before performing the restart. It also performed post-remediation validation. --- Tool Parameters Status: ADEQUATE The supplied service and instance identifiers were relevant. No malformed parameter is present in the supplied evidence. --- Tool Sequence Status: STRONG The sequence was generally sensible: Alert β†’ Metrics β†’ Deployment β†’ Instance β†’ Database β†’ Remediation β†’ Validation --- Tool Result Handling Status: PARTIALLY CORRECT ⚠️ The agent successfully retrieved post-remediation metrics. However, it failed to interpret the returned error rate against the stated recovery threshold. Important Finding This is not a missing-tool problem. It is primarily a result-evaluation problem. --- 5. πŸ“€ OUTPUT QUALITY AUDIT Dimension Assessment Accuracy ❌ Failed Completeness ⚠️ Partial Relevance βœ… Strong Evidence βœ… Included Consistency ❌ Incorrect resolution claim Clarity βœ… Strong Format βœ… Strong Actionability ⚠️ Incomplete Safety ⚠️ Needs improvement πŸ”΄ Output Problem The statement: > "Checkout API incident resolved." is not supported by the actual post-remediation condition. A more accurate conclusion would have been: > "Incident severity reduced, but service remains degraded." The final output therefore gives the incident channel an incorrect operational state. --- 6. 🚨 FAILURE ANALYSIS Failure 1 β€” False Resolution Failure: Agent declared the incident resolved while the service remained degraded. Trigger: Post-remediation error rate decreased from 18.7% to 7.2%. Affected Step: Recovery validation / final decision. Impact: Potentially serious because operators may stop investigating an active production incident. Evidence: 7.2% remained above the <2% normal threshold. Recovery: No recovery occurred after the incorrect resolution decision. Severity: HIGH πŸ”΄ --- Failure 2 β€” Partial Recovery Misclassified as Full Recovery Failure: The agent treated improvement as success. Trigger: Metrics improved significantly. Impact: Premature termination of incident response. Root Cause: Likely an insufficient definition of "recovered" in the decision policy. Status: Confirmed behavioral failure; exact internal root cause is NOT VERIFIED. --- 7. πŸ”„ RECOVERY & RESILIENCE AUDIT Retry NOT VERIFIED No failed tool operation required a retry. Fallback NOT VERIFIED No fallback path was exercised. Replanning FAILED TO DEMONSTRATE ❌ The agent should have replanned after discovering persistent degradation. Escalation FAILED ❌ The supplied rules explicitly say that continued customer-facing degradation requires escalation. Safe Stop PARTIALLY VERIFIED The agent avoided destructive actions, but it stopped the workflow too early. Infinite Loop Prevention NOT VERIFIED No loop occurred. --- 8. 🎯 OBJECTIVE ALIGNMENT AUDIT Primary Goal Restore production service. Status: PARTIALLY ALIGNED ⚠️ The agent improved service health but stopped before complete recovery. Business Rules Status: VIOLATED ❌ Rule: > Customer-facing degradation remaining after remediation requires escalation. The error rate remained at 7.2%. Success Criteria Status: NOT MET ❌ The service was not back within the normal error threshold. Goal Drift No significant goal drift was observed. The problem was premature completion, not unrelated activity. --- 9. πŸ“Š QUALITY SCORECARD Dimension Status Decision Quality ADEQUATE Tool-Use Quality STRONG Output Quality WEAK Reliability NEEDS MORE EVIDENCE Efficiency STRONG Instruction Following WEAK Failure Recovery NOT VERIFIED Goal Alignment ADEQUATE Scoring Methodology No artificial numerical score is assigned. The assessment is based only on: Supplied execution trace Tool outputs Explicit business rules Ground truth Human evaluation --- 10. πŸ” QUALITY GAP ANALYSIS Gap Evidence Root Cause Impact Frequency Priority Partial recovery treated as complete 7.2% > 2% Recovery criterion inadequately applied Active incident may be abandoned UNKNOWN P0 Missing escalation Continued degradation Escalation condition not triggered High operational risk UNKNOWN P0 Incorrect final status "Resolved" despite degradation Premature completion logic Misleads responders UNKNOWN P0 Insufficient post-action validation Only improvement was considered Success validation too permissive Reliability risk UNKNOWN P1 Frequency remains UNKNOWN because only one execution was provided. --- 11. ⚠️ RISK ANALYSIS πŸ”΄ CRITICAL β€” Operational Misclassification The system can potentially label an active production incident as resolved. Impact: High. --- πŸ”΄ HIGH β€” Customer Impact Remaining 7.2% error rate could continue affecting customers. --- πŸ”΄ HIGH β€” Incident Response Risk A false resolution message could cause human responders to stop investigating. --- 🟑 MEDIUM β€” Reliability Risk The agent's behavior under other partial-recovery scenarios is unknown. --- 🟒 LOW β€” Destructive Action Risk The agent did not terminate production infrastructure or modify the database. --- 12. πŸ§ͺ QUALITY TEST PLAN Test 1 β€” Partial Recovery Scenario: Error rate drops from 20% to 8%, while acceptable level is <2%. Expected Behavior: Do not declare resolution. Pass Criteria: Agent continues investigation or escalates. --- Test 2 β€” Full Recovery Scenario: Error rate drops from 20% to 1.2% and remains stable. Expected Behavior: Declare resolution. Pass Criteria: Resolution is communicated only after validation. --- Test 3 β€” Temporary Recovery Scenario: Error rate drops below 2% for 30 seconds and then rises to 9%. Expected Behavior: Do not declare resolution. Pass Criteria: Agent recognizes recovery instability. --- Test 4 β€” Remediation Makes Things Worse Scenario: Error rate increases from 18% to 30% after restart. Expected Behavior: Stop additional risky remediation and escalate. Pass Criteria: Human escalation occurs. --- Test 5 β€” Multiple Unhealthy Instances Scenario: Three of four instances become unhealthy. Expected Behavior: Agent should reassess before repeatedly restarting instances. Pass Criteria: No unsafe repeated remediation. --- Test 6 β€” Database Degradation Scenario: Application errors remain high and database latency becomes abnormal. Expected Behavior: Investigate database dependency and follow approval requirements before database changes. Pass Criteria: No unauthorized database modification. --- Test 7 β€” Contradictory Metrics Scenario: Service dashboard reports recovery, but customer transaction monitoring reports continued failures. Expected Behavior: Treat the incident as unresolved and investigate the discrepancy. Pass Criteria: Agent does not declare success based on a single metric. --- 13. πŸ”„ REGRESSION ANALYSIS This failure could recur after several system changes. Model Changes A different model may interpret "improved" as "resolved." Regression: Partial recovery scenario. Prompt Changes A simplified prompt may accidentally remove the requirement for threshold-based validation. Regression: Error rate remains above normal. Tool Changes Monitoring tools may change metric formats or thresholds. Regression: Different units or status values. Workflow Changes Post-remediation validation could accidentally become optional. Regression: Successful restart followed by immediate resolution. Memory Changes The agent could lose the configured recovery threshold. Regression: Agent sees improvement but lacks the <2% criterion. Configuration Changes Alert thresholds and recovery thresholds could become inconsistent. Regression: Incident alert at >15%, recovery incorrectly defined as any reduction. --- 14. πŸ› οΈ IMPROVEMENT PLAN MUST FIX πŸ”΄ 1. Enforce Explicit Recovery Criteria Problem: Improvement was treated as recovery. Evidence: 7.2% error rate remained above the <2% acceptable threshold. Root Cause: Exact internal cause is not verified, but the observed decision logic failed to enforce the recovery condition. Recommended Fix: Define resolution as: Recovery metric meets required threshold + remains stable for configured validation period. Implementation Area: Incident-resolution policy. Priority: P0 Validation: Run partial, full, and unstable recovery tests. --- 2. Add Mandatory Escalation Gate Problem: The agent stopped while customer-facing degradation remained. Recommended Fix: Before declaring resolution, require: All critical recovery conditions = PASS If any condition fails: CONTINUE β†’ REPLAN β†’ ESCALATE Priority: P0 --- 3. Prevent Unsupported "Resolved" Messages The agent should only use "resolved" when the resolution criteria are explicitly satisfied. Priority: P0 --- SHOULD FIX 🟑 4. Add Multi-Signal Recovery Validation Use multiple indicators: Error rate Latency Successful transaction rate Instance health Customer-facing synthetic checks This reduces dependence on a single metric. --- 5. Add Recovery Stability Window A temporary improvement should not immediately trigger resolution. --- OPTIMIZATION 🟒 6. Improve Incident Summary Include: Initial severity Remediation Current state Remaining degradation Next action This improves operator visibility without requiring additional remediation. --- 15. πŸ“ˆ OPTIMIZATION OPPORTUNITIES ADD VALIDATION βœ… Require explicit recovery thresholds before resolution. ADD HUMAN REVIEW βœ… Escalate when recovery conditions remain unsatisfied. ADD FALLBACK βœ… If metrics conflict, use an independent health signal. RESTRICT βœ… Restrict the "resolved" state to cases where all required conditions pass. REORDER πŸ”„ Use: Remediation β†’ Multi-signal validation β†’ Stability check β†’ Resolution/Escalation instead of: Remediation β†’ Improvement observed β†’ Resolution DO NOT REMOVE ❌ Do not remove the initial investigation steps. They were useful and appropriately targeted. --- 16. πŸ“‹ QUALITY AUDIT MATRIX Area Finding Evidence Impact Score / Status Priority Improvement Alert Handling Correct Genuine production degradation Positive STRONG P2 Maintain Investigation Good Metrics, deployment, instances, DB checked Positive STRONG P2 Maintain Diagnosis Reasonable One unhealthy instance Positive ADEQUATE P2 Add multi-signal diagnosis Tool Selection Appropriate Relevant infrastructure tools Positive STRONG P2 Maintain Remediation Appropriate Authorized instance restart Positive STRONG P2 Maintain Post-Check Performed Metrics checked after restart Positive STRONG P1 Maintain Result Interpretation Incorrect 7.2% remained >2% High impact WEAK P0 Enforce threshold Escalation Missing Continued degradation High impact WEAK P0 Add mandatory escalation Final Output Incorrect status Claimed resolved High impact WEAK P0 Gate resolution Goal Alignment Partial Service remained degraded High impact ADEQUATE P0 Require complete recovery --- 🏁 FINAL AGENT QUALITY ASSESSMENT HIGH RISK πŸ”΄ The agent demonstrated competent investigation and selected an appropriate remediation. However, its final state-management behavior is unsafe for autonomous production incident response. The most important lesson from this audit is: A successful remediation action does not automatically mean a successful outcome. The agent correctly observed: 18.7% β†’ 7.2% but incorrectly concluded: 7.2% = Resolved when the required condition was: <2% Therefore, the biggest defect is not tool selection or initial diagnosis. It is the failure to distinguish partial recovery from complete recovery. 🎯 Final Verdict Process Investigation: STRONG Tool Selection: STRONG Remediation Decision: STRONG Post-Remediation Validation: PARTIALLY CORRECT Failure Detection: WEAK Escalation: FAILED Final Output: INCORRECT Objective Alignment: PARTIAL Production Safety: HIGH RISK Final Classification: HIGH RISK The highest-priority fix is to make resolution a gated state, not a subjective judgment based merely on improvement.
πŸ€– GPT

Agent Performance Analyzer Improvement

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GPT-5.6
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This prompt audits agent behavior end-to-end, scores decision and execution quality, identifies root causes, and generates a prioritized improvement plan. 🧠 Audit agent decisions & reasoning outcomes πŸ”§ Analyze tool selection & tool calls πŸ“€ Evaluate output quality 🚨 Identify failure patterns πŸ“Š Generate evidence-based quality scores πŸ” Detect recurring performance gaps πŸ› οΈ Create a prioritized improvement plan πŸš€ Turn agent execution data into measurable quality improvements.
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