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.
npx skills add charlesjones-dev/claude-code-plugins-dev --skill performance-auditgit clone --depth 1 https://github.com/charlesjones-dev/claude-code-plugins-devWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/performance-audit)<a href="https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/performance-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/performance-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/performance-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/performance-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.06852 |
| Opus 5.5 | $0.00010 | $0.02741 |
| Sonnet 5.5 | $0.00005 | $0.01370 |
| Haiku 4.5 | $0.00003 | $0.00685 |
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 10d 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.
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
- Code Pattern Analysis: Scan for N+1 queries, inefficient loops, memory leaks, blocking operations
- Database Performance Review: Analyze queries, indexing strategies, and data access patterns
- Resource Utilization Assessment: Review memory allocation patterns, CPU-intensive operations, I/O bottlenecks
- Architecture Performance Analysis: Examine caching strategies, async patterns, connection pooling, concurrency
- Scalability Assessment: Identify thread pool issues, connection management, and load handling patterns
- 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
- Format:
- 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
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.
- 10d ago Changed · +4 tokens per session c13f0628bf59
- 1mo ago First seen · 794 lines · 21 tokens per session scan A bc5e115edc8c
performance-audit is a skill published in the GitHub repository charlesjones-dev/claude-code-plugins-dev (35 stars, last pushed 6d ago), licensed MIT. It adds 25 tokens to every session and 6,852 once invoked, about $0.0001 per session on Opus 5.5. 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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