agentmods.dev

perf-and-memory

perf-and-memory is a skill for Codex from ashermahonin/agentic-skills. It costs 84 tokens per session (456 once invoked), scanned A, original, MIT.

A method for investigating or planning software performance and memory work using measurements such as latency, throughput, CPU, memory, allocations, or startup time.

In plain words
What is it for?
Planning or reviewing profiling, benchmarks, caching, database queries, concurrency, allocation use, serialization, capacity, and runtime changes.
Why use it?
It prevents guesswork by identifying the actual bottleneck, measuring a baseline, and checking whether a change improved the chosen metric.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 10repo 2mo ago A scan 84 tokens original MIT

Good fit Planning or reviewing profiling, benchmarks, caching, database queries, concurrency, allocation use, serialization, capacity, and runtime changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ashermahonin/agentic-skills/perf-and-memory
View source ↗ ashermahonin/agentic-skills
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 ashermahonin/agentic-skills --skill perf-and-memory
Clone the repo
git clone --depth 1 https://github.com/ashermahonin/agentic-skills

Made for: Codex.

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 perf-and-memory

README.md
[![agentmods](https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/perf-and-memory/github.svg)](https://agentmods.dev/skills/ashermahonin/agentic-skills/perf-and-memory)
Your own site
<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/perf-and-memory"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/perf-and-memory/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.

agentmods 80×15 button for perf-and-memory

Your own site · 80×15
<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/perf-and-memory"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/perf-and-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 456 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.
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 $0.00084 $0.00456
Opus 5.5 $0.00034 $0.00182
Sonnet 5.5 $0.00017 $0.00091
Haiku 4.5 $0.00008 $0.00046

Measured 2mo ago against content hash 1600011db444, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

perf-and-memory 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 2mo 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.

agentic/skills/perf-and-memory/SKILL.md · 55 lines

What it actually says

Performance and Memory

Purpose

Keep performance work honest. Find the bottleneck with evidence, choose the simplest useful intervention, and make sure the result can be measured again.

Change context

  • Identify the user-visible or system-visible performance problem.
  • Choose the metric: latency, throughput, memory, CPU, allocations, query count, startup, bundle size, or cost.
  • Find existing benchmarks, traces, logs, or production signals.
  • Name the language/runtime constraints that matter.

Change method

  1. Form a hypothesis and measurement plan before optimizing.
  2. Collect baseline evidence or state why baseline cannot be collected.
  3. Look for algorithmic issues, I/O bottlenecks, query shape, caching boundaries, concurrency limits, allocation churn, and serialization overhead.
  4. Recommend or implement the smallest change likely to move the metric.
  5. Re-measure after the change when possible.
  6. Record tradeoffs: complexity, correctness risk, cache invalidation, resource cost, and rollback.

Engineering constraints

  • Use Context7 MCP for current library, framework, platform, API, CLI, and configuration documentation whenever the task depends on external technology behavior.

Evidence

  • Performance hypothesis
  • Baseline and target metric
  • Profiling or benchmark plan
  • Optimization recommendation
  • Validation evidence
  • Language profile update

Ready when

  • Never optimize an unnamed metric.
  • Do not claim improvement without measurement or a clear reason measurement was impossible.
  • Treat caching as a correctness and invalidation problem, not a magic speed button.
  • Prefer reducing work over hiding work.

Handoff

Hand off metric, evidence, changed constraints, and regression checks to implementation, QA, or review.

References

  • references/language-profile-template.md: Use this for language-specific performance notes.
Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2mo ago First seen · 55 lines · 84 tokens per session scan A 1600011db444

Subscribe to this mod's changes

perf-and-memory is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 84 tokens to every session and 456 once invoked, about $0.0003 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 2026-08-31.

Analytics and metrics
Related

perf-and-memory compared with skills from other repositories

perf-and-memory next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
perf-and-memoryashermahonin/agentic-skillsSkill102mo agoMITA84Codex
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code