ln-31-performance-optimizer

ln-31-performance-optimizer is a skill for Claude Code from levnikolaevich/claude-code-skills. It costs 34 tokens per session (2,323 once invoked), scanned A, original, MIT.

A skill for improving a measured performance problem, such as slow response time, low throughput, high memory or CPU use, or excessive input/output. It uses profiling and controlled experiments before keeping a change.

In plain words
What is it for?
Use it to profile a known problem, compare optimization experiments, and retain only changes supported by comparable measurements.
Why use it?
It helps ensure optimization work addresses a real bottleneck without sacrificing correctness or causing another regression.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the optimization-suite plugin — 5 skills shipped together

Good fit Use it to profile a known problem, compare optimization experiments, and retain only changes supported by comparable measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/levnikolaevich/claude-code-skills/ln-31-performance-optimizer
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.

Any agent
npx skills add levnikolaevich/claude-code-skills --skill ln-31-performance-optimizer
Clone the repo
git clone --depth 1 https://github.com/levnikolaevich/claude-code-skills

Made for: Claude Code.

Or install optimization-suite, the plugin that ships this one along with the rest of its 5 skills.

Wrote 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.

agentmods badge for ln-31-performance-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/levnikolaevich/claude-code-skills/ln-31-performance-optimizer.svg)](https://agentmods.dev/skills/levnikolaevich/claude-code-skills/ln-31-performance-optimizer)
Your own site
<a href="https://agentmods.dev/skills/levnikolaevich/claude-code-skills/ln-31-performance-optimizer"><img src="https://agentmods.dev/badge/skills/levnikolaevich/claude-code-skills/ln-31-performance-optimizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,323 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00034 $0.02323
Opus 5 $0.00017 $0.01162
Sonnet 5 $0.00007 $0.00465
Haiku 4.5 $0.00003 $0.00232

Measured 2d ago against content hash 84fdfe5330a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ln-31-performance-optimizer 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/optimization-suite/skills/ln-31-performance-optimizer/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Optimizer

Goal: Optimize only measured problems. Preserve correctness, isolate experiments, and retain a change only when comparable evidence shows that it improves the agreed metric without unacceptable regressions.

Execution contract: The ordered checkboxes are the Definition of Done. Track every item internally as PENDING, PROVEN with concrete evidence, CLEARED with evidence that its condition is absent, or UNPROVEN with a gap; reading, delegation, or tool failure is not proof. Reconcile items after each section. Before returning, resolve all PENDING and count only PROVEN and CLEARED; apply the skill's verdict and approval rules to every gap. Preserve user intent, scope, and existing authorization. Continue authorized work; ask only for consequential unresolved choices or required external approval. Scale depth to material risk without silently skipping checks. Preserve dependency and safety ordering; otherwise choose the verification method appropriate to each obligation.

Tool Routing

Need Preferred tool Use it when Fallback
Repository state and safe edit boundary Git status, diff, branch or worktree inspection, and repository instructions Always before profiling or editing Stop if user changes cannot be isolated safely
Baseline and final metric Existing benchmark, load test, reproducible command, or production-like replay The metric and workload reflect the reported problem Create the smallest local benchmark that reproduces the behavior without inventing production scale
Bottleneck evidence Existing profiler, tracing, query diagnostics, allocation tools, or OS-level metrics Locating CPU, memory, I/O, lock, query, network, or scheduler cost Targeted instrumentation with cleanup plan
Code path and blast radius Language server or host-native code intelligence Following hot symbols, callers, implementations, and affected contracts Narrow search plus direct inspection of definitions and consumers
Correctness and regressions Repository-defined tests, build, lint, type, and smoke commands Before and after every retained experiment Choose the smallest portfolio action when current evidence cannot detect the likely material regression
Runtime and dependency semantics Official documentation, release notes, and specifications matching installed versions A hypothesis depends on optimizer, runtime, database, framework, or library behavior Primary-source web research; otherwise mark the hypothesis UNVERIFIED

Read the full file on GitHub · 106 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 Changed · -23 lines · -11 tokens per session 84fdfe5330a5
  2. 8d ago First seen · 129 lines · 45 tokens per session scan A 54950bd87ea3

Subscribe to this mod's changes

ln-31-performance-optimizer is a skill published in the GitHub repository levnikolaevich/claude-code-skills (558 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 2,323 once invoked, about $0.0002 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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