Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/conorluddy/xclaude-pluginnpx agentmods add skills/conorluddy/xclaude-plugin/performance-profilingWrote 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/conorluddy/xclaude-plugin/performance-profiling)<a href="https://agentmods.dev/skills/conorluddy/xclaude-plugin/performance-profiling"><img src="https://agentmods.dev/badge/skills/conorluddy/xclaude-plugin/performance-profiling/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/conorluddy/xclaude-plugin/performance-profiling"><img src="https://agentmods.dev/badge/skills/conorluddy/xclaude-plugin/performance-profiling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00052 | $0.07043 |
| Opus 5.5 | $0.00021 | $0.02817 |
| Sonnet 5.5 | $0.00010 | $0.01409 |
| Haiku 4.5 | $0.00005 | $0.00704 |
Grade A, and why
performance-profiling scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
api.fetch(limit: pageSize, offset: offset) How it starts
The opening of the file, as written. The whole thing — 1,208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Profiling Skill
Comprehensive guide to iOS performance analysis and optimization
Overview
Performance profiling is the systematic analysis of an iOS app's runtime behavior to identify bottlenecks, memory issues, network inefficiencies, and energy consumption patterns. This Skill guides you through using Instruments templates, interpreting profiling data, and applying optimization strategies.
Key Tools:
- Instruments (Xcode's profiling suite)
- xcodebuild for profiling builds
- Performance metrics analysis
- Memory graph debugging
When to Use This Skill
Use performance profiling when:
-
App Performance Issues
- Slow app launch times
- Choppy scrolling or animations
- UI freezing or unresponsiveness
- High CPU usage
-
Memory Problems
- Memory leaks detected
- Growing memory footprint
- Memory warnings
- App crashes due to memory pressure
-
Network Inefficiencies
- Slow data loading
- Excessive network requests
- Large payload sizes
- Poor offline handling
-
Energy Consumption
- Battery drain complaints
- Background processing issues
- Thermal throttling
- Energy impact reports
-
Pre-Release Optimization
- Performance regression detection
- Baseline performance establishment
- Release candidate validation
- Performance budget enforcement
Key Concepts
Instruments Templates
Time Profiler
- Measures CPU usage and call stacks
- Identifies hot paths in code
- Shows function-level performance
- Best for: CPU-bound operations, algorithm optimization
Allocations
- Tracks memory allocations and deallocations
- Shows object lifetime and retention
- Identifies memory growth patterns
- Best for: Memory footprint analysis, allocation hotspots
Leaks
- Detects memory leaks in real-time
- Shows leaked objects and their origins
- Identifies retain cycles
- Best for: Finding memory leaks, debugging reference cycles
Network
- Monitors HTTP/HTTPS traffic
- Shows request/response timing
- Tracks payload sizes
- Best for: API optimization, bandwidth analysis
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.
- 1mo ago First seen · 1,208 lines · 52 tokens per session scan A 48b0cb66ca26
performance-profiling is a skill published in the GitHub repository conorluddy/xclaude-plugin (184 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 7,043 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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