configure-memory-profiling

configure-memory-profiling is a skill for Claude Code, Codex from laurigates/claude-plugins. It costs 34 tokens per session (2,010 once invoked), scanned A, original, MIT.

A Python memory-profiling setup using pytest-memray. Memory profiling measures how much memory code allocates and can reveal leaks or unexpectedly large usage.

In plain words
What is it for?
Use it to configure memory checks for pytest, set allocation limits and benchmarks, detect leaks, add CI checks, and inspect memory used by native C extensions.
Why use it?
It helps catch memory regressions during tests and prevents changes from quietly increasing a program's memory use.

Skill for Claude CodeCodex

Part of the configure-plugin plugin — 48 skills shipped together

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/laurigates/claude-plugins/configure-memory-profiling
Any agent
npx skills add laurigates/claude-plugins --skill configure-memory-profiling
Clone the repo
git clone --depth 1 https://github.com/laurigates/claude-plugins

Made for: Claude Code, Codex.

Or install configure-plugin, the plugin that ships this one along with the rest of its 48 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 configure-memory-profiling

README.md
[![agentmods](https://agentmods.dev/badge/skills/laurigates/claude-plugins/configure-memory-profiling.svg)](https://agentmods.dev/skills/laurigates/claude-plugins/configure-memory-profiling)
Your own site
<a href="https://agentmods.dev/skills/laurigates/claude-plugins/configure-memory-profiling"><img src="https://agentmods.dev/badge/skills/laurigates/claude-plugins/configure-memory-profiling.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 2,010 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 $0.00034 $0.02010
Opus 5 $0.00017 $0.01005
Sonnet 5 $0.00007 $0.00402
Haiku 4.5 $0.00003 $0.00201

Measured yesterday against content hash 43896dfc4d98, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

configure-memory-profiling 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 yesterday.

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.

configure-plugin/skills/configure-memory-profiling/SKILL.md · 199 lines

How it starts

The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/configure:memory-profiling

Check and configure memory profiling infrastructure for Python projects using pytest-memray.

When to Use This Skill

Use this skill when... Use another approach when...
Setting up memory profiling for a Python project from scratch Project is not Python — memray/pytest-memray are Python-only
Adding pytest-memray integration for CI memory regression detection Profiling CPU performance — use cProfile or py-spy instead
Configuring memory leak detection in test suites Running load/stress tests — use /configure:load-tests
Setting memory thresholds and allocation benchmarks for CI Quick one-off memory check — run uv run pytest --memray directly
Enabling native C extension stack tracking for deep profiling Profiling production systems live — use memray standalone or Grafana

Context

  • Project root: !pwd
  • Python project: !find . -maxdepth 1 \( -name 'pyproject.toml' -o -name 'setup.py' \)
  • pytest-memray installed: !find . -maxdepth 1 \( -name 'pyproject.toml' -o -name 'requirements*.txt' \) -exec grep 'pytest-memray' {} +
  • memray installed: !find . -maxdepth 1 \( -name 'pyproject.toml' -o -name 'requirements*.txt' \) -exec grep 'memray' {} +
  • Conftest fixtures: !find . -path '*/tests/*' -maxdepth 2 -name 'conftest.py' -exec grep -l 'memray' {} +
  • Memory test files: !find . -path '*/tests/*' -maxdepth 3 -name '*memory*' -o -name '*memray*'
  • Benchmark tests: !find . -path '*/tests/*' -maxdepth 3 -type d -name 'benchmarks'
  • CI workflows: !find . -path '*/.github/workflows/*' -maxdepth 3 -name '*memory*'
  • Memory reports dir: !find . -maxdepth 1 -type d -name 'memory-reports'

Parameters

Parse from $ARGUMENTS:

  • --check-only: Report memory profiling compliance status without modifications
  • --fix: Apply all fixes automatically without prompting
  • --threshold <mb>: Set default memory threshold in MB (default: 100)
  • --native: Enable native stack tracking for C extensions

Read the full file on GitHub · 199 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. yesterday First seen · 199 lines · 34 tokens per session scan A 43896dfc4d98

Subscribe to this mod's changes

configure-memory-profiling is a skill published in the GitHub repository laurigates/claude-plugins (57 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 2,010 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 2026-09-03.

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