How do I install the Performance Auditor skill?

Run npx skillmds@latest add willianbs/performance-auditor in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Performance Auditor safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Performance Auditor?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Performance Auditor free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Performance Auditor?

willianbs (@willianbs) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Performance Auditor by willianbs — Agent Skill

Name: Performance Auditor
Author: willianbs

Performance Auditor

Evidence-based performance and scalability audit against SLOs and budgets. Use for slow paths, capacity risk, or review escalation. Emits PERF_REPORT. Never micro-optimizes without measurement or recommends changes below the noise floor.

willianbs 4edff80 2 files · 3.6 KB Updated Sep 17, 2026

File contents

Purpose

Find performance risks that matter, measured against baselines or SLOs—not folklore.

When to Use / When NOT to Use

Use when: latency/throughput complaints, hot paths, large list UIs, N+1 suspects, scaling concerns, quality-gate escalation.

Do not use when: no performance signal and change is trivial; pure security review.

Preconditions

Scope (endpoint, page, job) identified. Prefer CONTEXT_PACK + metrics or permission to measure.

Inputs / Outputs

Inputs: scope, SLOs/budgets if any, profiling/RUM/load data, diff.

Outputs: PERF_REPORT

Upstream / Downstream

Upstream: code-reviewer, feature-implementer, defect-analyst, quality-gate.

Downstream: feature-implementer, delivery-planner, quality-gate.

Core Principles

Measure before optimize.
Attach findings to SLOs/budgets when they exist.
Choose frontend vs backend profile—don’t dump both blindly.
No action if improvement < noise floor.
Tradeoffs explicit (complexity, cache coherence, cost).
Scalability ≠ micro-opt.
Confidence ≤ Medium without baseline numbers.

Process

Select profile: frontend (LCP/INP/bundle/waterfalls) or backend (p95, QPS, DB, allocations, concurrency) or both if full-stack path.
Establish baseline — existing metrics, logs, or request a measurement. Without baseline → mark confidence accordingly.
Find bottlenecks — N+1, chatty I/O, unbounded work, sync-on-async, huge payloads, missing pagination, cache misses.
Scalability — what breaks at 10×.
Recommendations — expected benefit (qualitative OK if labeled), risk, validation method.
No-action when variance is noise or user experience already within SLO.

Evidence Requirements

Cite metrics, traces, or code paths. Critical = SLO breach, OOM, or meltdown risk with evidence.

Stop Conditions / Failure Modes

Condition	Action
No baseline and cannot measure	Report with Low/Medium confidence; avoid Critical claims
Within SLO and no headroom issue	Decision Proceed; empty or Info findings

Severity + Confidence

Portfolio standard. Critical reserved for outage/SLO-breach class risks.

Output Contract

## PERF_REPORT
Profile: frontend | backend | full-stack
SLO/budget: ...
Baseline: ...
Findings: ...
No-action rationale (if any): ...
Release impact: Proceed | ProceedWithConditions | Block
Decision: ...

Handoffs

feature-implementer — apply fixes
quality-gate — consume PERF_REPORT
defect-analyst — if perf bug needs causal depth

Never

Never recommend micro-opts without data.
Never ignore algorithmic/IO issues to tweak syntax.
Never claim “10× faster” without measurement plan.

---name: performance-auditordescription: Evidence-based performance and scalability audit against SLOs and budgets. Use for slow paths, capacity risk, or review escalation. Emits PERF_REPORT. Never micro-optimizes without measurement or recommends changes below the noise floor.---# PurposeFind performance risks that matter, measured against baselines or SLOs—not folklore.# When to Use / When NOT to Use**Use when:** latency/throughput complaints, hot paths, large list UIs, N+1 suspects, scaling concerns, quality-gate escalation.**Do not use when:** no performance signal and change is trivial; pure security review.# PreconditionsScope (endpoint, page, job) identified. Prefer CONTEXT_PACK + metrics or permission to measure.# Inputs / Outputs**Inputs:** scope, SLOs/budgets if any, profiling/RUM/load data, diff.**Outputs:** `PERF_REPORT`# Upstream / Downstream**Upstream:** code-reviewer, feature-implementer, defect-analyst, quality-gate.**Downstream:** feature-implementer, delivery-planner, quality-gate.# Core Principles1. Measure before optimize.2. Attach findings to SLOs/budgets when they exist.3. Choose frontend vs backend profile—don’t dump both blindly.4. No action if improvement < noise floor.5. Tradeoffs explicit (complexity, cache coherence, cost).6. Scalability ≠ micro-opt.7. Confidence ≤ Medium without baseline numbers.# Process1. Select profile: **frontend** (LCP/INP/bundle/waterfalls) or **backend** (p95, QPS, DB, allocations, concurrency) or both if full-stack path.2. Establish baseline — existing metrics, logs, or request a measurement. Without baseline → mark confidence accordingly.3. Find bottlenecks — N+1, chatty I/O, unbounded work, sync-on-async, huge payloads, missing pagination, cache misses.4. Scalability — what breaks at 10×.5. Recommendations — expected benefit (qualitative OK if labeled), risk, validation method.6. **No-action** when variance is noise or user experience already within SLO.# Evidence RequirementsCite metrics, traces, or code paths. Critical = SLO breach, OOM, or meltdown risk with evidence.# Stop Conditions / Failure Modes| Condition | Action ||-----------|--------|| No baseline and cannot measure | Report with Low/Medium confidence; avoid Critical claims || Within SLO and no headroom issue | Decision Proceed; empty or Info findings |# Severity + ConfidencePortfolio standard. Critical reserved for outage/SLO-breach class risks.# Output Contract```## PERF_REPORTProfile: frontend | backend | full-stackSLO/budget: ...Baseline: ...Findings: ...No-action rationale (if any): ...Release impact: Proceed | ProceedWithConditions | BlockDecision: ...```# Handoffs- **feature-implementer** — apply fixes- **quality-gate** — consume PERF_REPORT- **defect-analyst** — if perf bug needs causal depth# Never- Never recommend micro-opts without data.- Never ignore algorithmic/IO issues to tweak syntax.- Never claim “10× faster” without measurement plan.

Frequently asked questions