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.
Install with Tessl CLI
npx tessl i github:wshobson/agents --skill debugging-strategies72
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillAgent success when using this skill
Validation for skill structure
Python performance profiling
cProfile used
100%
90%
pstats Stats used
100%
75%
sort_stats cumulative
100%
100%
print_stats called
100%
87%
Profile output included
100%
100%
Measurement before fix
100%
100%
Measurement after fix
100%
100%
Root cause identified
100%
100%
Root cause fixed
100%
100%
Findings documented
100%
100%
Without context: $0.3556 · 2m 1s · 10 turns · 11 in / 6,461 out tokens
With context: $0.7724 · 3m 39s · 22 turns · 71 in / 12,157 out tokens
Systematic bug investigation
Observations documented
100%
100%
Hypotheses stated
30%
50%
Experiment described
80%
90%
Analysis included
100%
100%
Root cause identified
100%
100%
Root cause fixed
100%
100%
Single targeted change
75%
62%
No debug artifacts
100%
100%
Information gathered
90%
100%
Findings documented
100%
100%
Without context: $0.3584 · 1m 47s · 13 turns · 13 in / 5,493 out tokens
With context: $0.7233 · 2m 57s · 23 turns · 419 in / 9,467 out tokens
Production incident investigation
No production changes
100%
100%
Evidence gathering first
100%
100%
Staging before prod
100%
100%
Differential table
33%
100%
Recent changes checked
100%
100%
Hypotheses formed
100%
100%
Failure modes covered
100%
100%
Local reproduction steps
87%
87%
git bisect commands
100%
100%
Bisect test described
100%
100%
Without context: $0.2930 · 2m · 8 turns · 9 in / 5,849 out tokens
With context: $0.5396 · 2m 57s · 16 turns · 304 in / 8,384 out tokens
Table of Contents
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