algorithmic-complexity-review

algorithmic-complexity-review is a skill for Claude Code, Codex from pproenca/dot-skills. It costs 173 tokens per session (3,023 once invoked), scanned A, original, MIT.

A code-review workflow for finding algorithmic complexity problems, meaning code that becomes disproportionately slower or uses more memory as its input grows. It covers languages such as Python, JavaScript, TypeScript, Java, and Go.

In plain words
What is it for?
Use it to review pull requests, investigate slow functions, or refactor code that processes growing lists, trees, streams, or user-scaled input.
Why use it?
It identifies common causes of slow production code, including nested loops, repeated database queries, exponential recursion, and quadratic string or collection building. It helps connect the suspicious code pattern to its likely performance cost.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review pull requests, investigate slow functions, or refactor code that processes growing lists, trees, streams, or user-scaled input.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pproenca/dot-skills/algorithmic-complexity-review
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 pproenca/dot-skills --skill algorithmic-complexity-review
Clone the repo
git clone --depth 1 https://github.com/pproenca/dot-skills

Made for: Claude Code, 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 algorithmic-complexity-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/pproenca/dot-skills/algorithmic-complexity-review.svg)](https://agentmods.dev/skills/pproenca/dot-skills/algorithmic-complexity-review)
Your own site
<a href="https://agentmods.dev/skills/pproenca/dot-skills/algorithmic-complexity-review"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/algorithmic-complexity-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 173 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,023 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 $0.00173 $0.03023
Opus 5 $0.00086 $0.01511
Sonnet 5 $0.00035 $0.00605
Haiku 4.5 $0.00017 $0.00302

Measured 5d ago against content hash 42ed154425ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

algorithmic-complexity-review 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 5d 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.

skills/.experimental/algorithmic-complexity-review/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dot-skills Algorithmic Complexity (Big-O) Best Practices

Find, classify, and fix algorithmic complexity (Big-O) problems in code — language-agnostic. The 39 rules across 8 categories cover the patterns responsible for the vast majority of accidental quadratic, exponential, and N+1 blowups in production code: nested iteration, loop-invariant I/O, data-structure mismatch, recursion explosions, redundant computation, collection-building anti-patterns, search/sort selection, and space traps.

When to Apply

Use this skill when:

  • Reviewing a pull request or function for performance regressions
  • Asked "why is this slow?" or "can we make this faster?"
  • Refactoring a hot path or a function that handles user-scaled input
  • Reading code that contains: nested loops, .includes/.find/x in list inside iteration, ORM access in a loop, recursion without memoization, string/array building via += or spread, file/database I/O inside iteration
  • Reviewing code that processes lists, trees, or streams whose size will grow

Workflow: Find, Classify, Fix

The skill is structured for a three-step workflow on any code under review:

1. Find — Scan for the Suspicion Patterns

Look for these structural signals first (highest hit rate):

Signal Likely Category First Rule to Check
Two nested for loops nested- nested-explicit-quadratic-loops
.includes / .find / x in list inside a loop nested- nested-includes-in-loop
ORM access inside a loop (for o in orders: o.customer.x) io- io-n-plus-one-query
await fetch in for-of io- io-sequential-await-in-loop
array.find to "join" two arrays ds- ds-hashmap-for-keyed-access
Recursive function with overlapping arguments rec- rec-memoize-overlapping-subproblems
s = s + part or [...acc, x] in a loop build- build-avoid-quadratic-string-concat, build-avoid-spread-in-reducer
sorted(...) called inside a loop search- search-sort-once-outside-loop
readlines() / loading whole files space- space-stream-dont-load

Read the full file on GitHub · 168 lines

Files

What ships with it

44 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. 5d ago First seen · 168 lines · 173 tokens per session scan A 42ed154425ba

Subscribe to this mod's changes

algorithmic-complexity-review is a skill published in the GitHub repository pproenca/dot-skills (203 stars, last pushed 23d ago), licensed MIT. It adds 173 tokens to every session and 3,023 once invoked, about $0.0009 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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