Perf Analyzer
- 2 installs
- 931 repo stars
- Updated July 26, 2026
- avifenesh/awesome-slash
perf-analyzer is a skill that synthesizes performance investigation results (baselines, experiments, profiling) into evidence-backed recommendations and next steps.
About
This skill synthesizes the results of a performance investigation into clear, evidence-backed recommendations. A developer uses it at the end of a perf study, feeding it baseline data, experiment results, profiling evidence, and tested hypotheses. It outputs a summary, recommendations, abandoned hypotheses, and next steps, and it only cites evidence that exists in logs or code.
- Synthesizes perf investigation results into evidence-backed recommendations
- Takes baselines, experiment results, profiling evidence, and tested hypotheses as inputs
- Only cites evidence present in logs or code; requests a re-run when data is insufficient
Perf Analyzer by the numbers
- 2 all-time installs (skills.sh)
- Ranked #467 of 596 Debugging skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
perf-analyzer capabilities & compatibility
- Capabilities
- performance analysis · recommendation synthesis · debugging
- Use cases
- debugging · data analysis
What perf-analyzer says it does
Synthesize performance investigation results into clear recommendations.
Only cite evidence that exists in logs or code.
If data is insufficient, say so and request a re-run.
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| Installs | 2 |
|---|---|
| repo stars | ★ 931 |
| Last updated | July 26, 2026 |
| Repository | avifenesh/awesome-slash ↗ |
What it does
Turn baseline, experiment, and profiling evidence from a performance investigation into concrete recommendations.
Who is it for?
Developers wrapping up a performance investigation who need to convert raw evidence into decisions.
Skip if: Running benchmarks or profilers directly; this skill only synthesizes results others produce.
When should I use this skill?
You are synthesizing perf findings into evidence-backed recommendations and decisions.
What you get
A summary, prioritized recommendations, abandoned hypotheses, and clear next steps grounded only in real evidence.
- performance recommendations
- abandoned-hypothesis list
- next-steps
By the numbers
- outputs a 2-3 sentence summary
- part of a multi-skill perf investigation pipeline
Files
perf-analyzer
Synthesize performance investigation results into clear recommendations.
Follow docs/perf-requirements.md as the canonical contract.
Inputs
- Baseline data
- Experiment results
- Profiling evidence
- Hypotheses tested
- Breaking point results
Output Format
summary: <2-3 sentences>
recommendations:
- <actionable recommendation 1>
- <actionable recommendation 2>
abandoned:
- <hypothesis or experiment that failed>
next_steps:
- <if user should continue or stop>Constraints
- Only cite evidence that exists in logs or code.
- If data is insufficient, say so and request a re-run.
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What inputs does it need?
Baseline data, experiment results, profiling evidence, hypotheses tested, and breaking point results.
What if the data is insufficient?
The skill says so and requests a re-run rather than inventing conclusions.