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| author | Arpit Chakladar <arpit@chakladar.me> | 2026-09-29 23:45:25 +0530 |
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| committer | Arpit Chakladar <arpit@chakladar.me> | 2026-09-29 23:45:25 +0530 |
| commit | 33519df0fff478526d217d04190577b33c5bf7d0 (patch) | |
| tree | 18f6ee9bb8101381212038d16099e59d250b7080 /modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md | |
| parent | 7975de6d03289bcc143137d5458486def5adc672 (diff) | |
| parent | 871a29efd370088f669c4f2b9e20b8992406a444 (diff) | |
| download | home-manager-config-33519df0fff478526d217d04190577b33c5bf7d0.tar.gz home-manager-config-33519df0fff478526d217d04190577b33c5bf7d0.zip | |
Merge branch 'adding-pi-harness'
Diffstat (limited to 'modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md')
| -rw-r--r-- | modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md | 37 |
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diff --git a/modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md b/modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md new file mode 100644 index 0000000..0a65471 --- /dev/null +++ b/modules/development/pi-coding-agent/skills/performance-analysis/SKILL.md @@ -0,0 +1,37 @@ +--- +name: performance-analysis +description: "Measure before optimizing, identify likely bottlenecks, make a targeted change, and verify the effect." +--- + +# Performance Analysis Skill + +Measure before optimizing, identify likely bottlenecks, make a targeted change, and verify the effect. + +## Subagents +When you need to delegate sub‑tasks, use the `pi-subagents` skill. + +**Example:** To optimize a slow endpoint, run a **scout** to profile CPU usage in the `handler` function, another **scout** to measure I/O latency in the `storage` layer, and an **implementer** to apply algorithmic improvements while a **reviewer** compares benchmarks against the baseline. + +*You may adapt the delegation pattern to fit the exact requirements of the codebase.* + +## Workflow + +### 1. Measure +- Profile before changes +- Establish baseline metrics +- Identify hot paths + +### 2. Analyze +- Find actual bottlenecks +- Distinguish CPU vs I/O vs memory +- Consider algorithmic complexity + +### 3. Target +- One bottleneck at a time +- Minimal, focused change +- Prefer algorithmic improvements + +### 4. Verify +- Re-measure after change +- Compare to baseline +- Check for regressions |
