debugging-strategies

Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.

1.01x

Quality

51%

Does it follow best practices?

Impact

95%

1.01x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

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Evaluation results

96%

-4%

Slow Report Aggregation Investigation

Python performance profiling

Criteria

Without context

With context

cProfile used

100%

90%

pstats Stats used

100%

75%

sort_stats cumulative

100%

print_stats called

100%

87%

Profile output included

100%

Measurement before fix

100%

Measurement after fix

100%

Root cause identified

100%

Root cause fixed

100%

Findings documented

100%

91%

Order Processing Service Bug

Systematic bug investigation

Criteria

Without context

With context

Observations documented

100%

Hypotheses stated

30%

50%

Experiment described

80%

90%

Analysis included

100%

Root cause identified

100%

Root cause fixed

100%

Single targeted change

75%

62%

No debug artifacts

100%

Information gathered

90%

100%

Findings documented

100%

99%

Payment Checkout Failure Investigation

Production incident investigation

Criteria

Without context

With context

No production changes

100%

Evidence gathering first

100%

Staging before prod

100%

Differential table

33%

100%

Recent changes checked

100%

Hypotheses formed

100%

Failure modes covered

100%

Local reproduction steps

87%

git bisect commands

100%

Bisect test described

100%

Repository: Dicklesworthstone/pi_agent_rust
Commit: 47823e3

Evaluated: about 1 month ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Slow Report Aggregation Investigation Order Processing Service Bug Payment Checkout Failure Investigation

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