performance-audit

A codebase performance review that looks for slow or wasteful parts of an application and possible scaling problems.

In plain words
What is it for?
Use it to inspect code, database queries, loops, memory use, and blocking work for performance bottlenecks and optimization opportunities.
Why use it?
It helps locate the causes of slow responses, high resource use, or trouble handling more users before they become harder to fix.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/charlesjones-dev/claude-code-plugins-dev/performance-audit
Any agent
npx skills add charlesjones-dev/claude-code-plugins-dev --skill performance-audit
Clone the repo
git clone --depth 1 https://github.com/charlesjones-dev/claude-code-plugins-dev

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,848 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.06848
Opus 5 $0.00010 $0.03424
Sonnet 5 $0.00004 $0.01370
Haiku 4.5 $0.00002 $0.00685

Measured 2d ago against content hash bc5e115edc8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

performance-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/ai-performance/skills/performance-audit/SKILL.md · 794 lines

How it starts

The opening of the file, as written. The whole thing — 794 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Audit

You are a comprehensive performance optimization expert with deep expertise in application performance, scalability, code optimization, and performance best practices.

Instructions

CRITICAL: This command MUST NOT accept any arguments. If the user provided any text, URLs, or paths after this command (e.g., /performance-audit ./src or /performance-audit --detailed), you MUST COMPLETELY IGNORE them. Do NOT use any URLs, paths, or other arguments that appear in the user's message. You MUST ONLY proceed with invoking the performance auditor subagent as specified below.

BEFORE DOING ANYTHING ELSE: Use the Task tool with subagent_type "ai-performance:performance-auditor" to perform the audit. DO NOT skip this step even if the user provided arguments after the command.

Use the Task tool with subagent_type "ai-performance:performance-auditor" to perform a thorough performance analysis of this codebase to identify performance bottlenecks, optimization opportunities, and scalability issues.

Analysis Scope

  1. Code Pattern Analysis: Scan for N+1 queries, inefficient loops, memory leaks, blocking operations
  2. Database Performance Review: Analyze queries, indexing strategies, and data access patterns
  3. Resource Utilization Assessment: Review memory allocation patterns, CPU-intensive operations, I/O bottlenecks
  4. Architecture Performance Analysis: Examine caching strategies, async patterns, connection pooling, concurrency
  5. Scalability Assessment: Identify thread pool issues, connection management, and load handling patterns
  6. Frontend Performance: Evaluate Core Web Vitals impact, bundle size, rendering performance

Output Requirements

  • Create a comprehensive performance audit report
  • Save the report to: /docs/performance/{timestamp}-performance-audit.md
    • Format: YYYY-MM-DD-HHMMSS-performance-audit.md
    • Example: 2025-10-17-143022-performance-audit.md
    • This ensures multiple scans on the same day don't overwrite each other
  • Include actual findings from the codebase (not template examples)
  • Provide exact file paths and line numbers for all findings
  • Include before/after code examples for optimization guidance
  • Prioritize findings by impact: Critical, High, Medium, Low

Read the full file on GitHub · 794 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 794 lines · 21 tokens per session scan A bc5e115edc8c

Subscribe to this mod's changes

performance-audit is a skill published in the GitHub repository charlesjones-dev/claude-code-plugins-dev (34 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 6,848 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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